Medical History, Medication Use, and Risk of Nasopharyngeal Carcinoma

Medical History, Medication Use, and Risk of Nasopharyngeal Carcinoma Abstract Because persistent inflammation may render the nasopharyngeal mucosa susceptible to carcinogenesis, chronic ear-nose-throat (ENT) disease and its treatment might influence the risk of nasopharyngeal carcinoma (NPC). Existing evidence is, however, inconclusive and often based on methodologically suboptimal epidemiologic studies. In a population-based case-control study in southern China, we enrolled 2,532 persons with NPC and 2,597 controls, aged 20–74 years, from 2010 to 2014. Odds ratios were estimated for associations between NPC risk and history of ENT and related medications. Any history of chronic ENT disease was associated with a 34% increased risk of NPC. Similarly, use of nasal drops or aspirin was associated with approximately doubled risk of NPC. However, in secondary analyses restricted to chronic ENT diseases and related medication use at least 5 years prior to diagnosis/interview, most results were statistically nonsignificant, except a history of uncured ENT diseases, untreated nasal polyps, and earlier age at first diagnosis of ENT disease and first or most recent aspirin use. Overall, these findings suggest that ENT disease and related medication use are most likely early indications rather than causes of NPC, although the possibility of a modestly increased NPC risk associated with these diseases and related medications cannot be excluded. case-control study, medical history, medication use, nasopharyngeal carcinoma Nasopharyngeal carcinoma (NPC) has a remarkable geographical and racial/ethnic distribution, and it is endemic in parts of southern China. Numerous studies have suggested that NPC develops through interactions among genetic and environmental factors and Epstein-Barr virus (EBV) infection. The etiologic role of EBV in NPC is supported by molecular analyses, as well as by serological studies (1, 2). Assumed environmental risk factors for NPC include salted fish consumption, smoking, and poor oral health (3, 4), while genetic studies have consistently shown that certain human leukocyte antigens influence NPC risk (5). Inflammation has been proposed as one of the hallmarks of cancer (6), and persistent inflammation and infection of the respiratory tract in particular may render the nasopharyngeal mucosa more susceptible to carcinogenesis. Individual history of ear-nose-throat (ENT) disease, including sinusitis and otitis media, has been shown to increase NPC risk (7–11). Modern medicines, such as aspirin and nasal drops, as well as traditional herbal medicines, such as balms and essential oils, are commonly used in southern China to relieve symptoms of headache and nasal obstruction. Nasal balms or oils may increase NPC risk (12), whereas an inverse association between aspirin use and NPC risk has been reported (13). However, published studies of the use of these medications were either small in size or hospital-based, and observed associations may be due to reverse causality, recall bias, or confounding by underlying ENT disease. To fill the existing knowledge gap regarding the possible relationship of medical history and medication use with NPC risk, we conducted a large, population-based case-control study in southern China, where NPC is endemic. This study enabled a more rigorous investigation of the potential independent etiologic roles of ENT-related medical history and medication use in NPC development. METHODS Study population The NPC Genes, Environment, and EBV study (NPCGEE) is a collaborative population-based case-control study of NPC based in the Zhaoqing area of Guangdong Province and in the Wuzhou and Guiping/Pingnan areas of Guangxi Autonomous Region. These areas encompass 13 cities/counties (Deqing, Fengkai, Gaoyao, Huaiji, Sihui, Zhaoqing, Guangning, Wuzhou, Cenxi, Cangwu, Tengxian, Pingnan, and Guiping) in southern China, with a total population of approximately 8 million. Recruitment of cases and controls was described previously (14). In brief, cases were aged 20–74 years at diagnosis between March 2010 and December 2013, living in the described geographic area, and without a prior history of malignant disease or congenital or acquired immunodeficiency. All cases were histopathologically confirmed by pathology reports. We established a rapid case-ascertainment system including 10 hospitals and 2 cancer research institutions that directly notified study investigators of newly diagnosed NPC cases. In the Zhaoqing area, 1,528 eligible cases were identified between March 2010 and August 2013; in the Wuzhou area, 792 eligible cases were identified between April 2010 and September 2013; in the Guiping/Pingnan area, 727 eligible cases were identified between July 2010 and December 2013. The number of cases identified in each region was close to the expected number of incident NPC cases based on historical incidence rates. Of eligible patients who were contacted by study staff, 1,306 (85% of 1,528 cases) in the Zhaoqing area, 689 (87% of 792 cases) in the Wuzhou area, and 559 (77% of 727 cases) in the Guiping/Pingnan area were enrolled in the study. Controls were randomly selected every 6–12 months between November 2010 and November 2014 from continuously updated total population registries covering the Zhaoqing, Wuzhou, and Guiping/Pingnan populations, with frequency matching to the 5-year-age and sex distribution of the cases according to geographic region. Eligible controls were required to be residents of the study area without a prior history of malignant disease or congenital or acquired immune deficiency. Controls who had worked outside of the study area for 10 years or more, as identified with the help of the local government in each town or community, were not considered part of the study base, because they were highly unlikely to return to the study area if they were diagnosed with NPC; therefore, they were replaced. Of 3,932 potential controls selected from the total population registries, 730 (19%) could not be linked to an identifiable person because of invalid contact information. Of the 3,202 who were identified, 138 (4%) had emigrated out of the study area, 90 (3%) were deceased or incapacitated, and 326 (10%) refused to participate. Of the 2,648 (83% of 3,202) enrolled controls, 2,133 (81%) were initial selections from the population registry, and the other 515 (19%) were replacements. This study was approved by the institutional review boards of Sun Yat-sen University Cancer Center, the Institute for Viral Disease Control and Prevention of the Chinese Center for Disease Control and Prevention, Guangxi Medical University, and Harvard T.H. Chan School of Public Health, as well as the Regional Research Ethics Vetting Board in Stockholm, Sweden. All subjects granted written or oral informed consent to participate. Data collection Trained interviewers used a structured electronic questionnaire to conduct audiotaped face-to-face or telephone interviews with study participants. Although blinding to case-control status was not feasible, in an effort to reduce information bias, we required all interviewers, who were unaware of the study hypotheses, to interview an approximately equal number of cases and controls. The questionnaire covered demographic characteristics, residential history, occupational history, medical history of chronic ENT disease, medication use, family medical history, dietary habits, cigarette smoking, alcohol and tea drinking, and use of Chinese herbal medicine, among other topics. Questionnaire data were automatically flagged for logic errors and missing values, and errors were corrected by making comparisons against audio recordings or by contacting participants again. Five chronic ENT diseases were investigated: chronic sinusitis, chronic pharyngitis, chronic otitis media, nasal polyps, and septal abnormalities. For each disease, questions addressed whether the subject had ever been diagnosed (yes or no), age at diagnosis, number of times of diagnosed, age at most recent occurrence, any use of medications or surgical treatment, and whether the disease had been cured (i.e., was no longer symptomatic). Persistent, chronic ENT disease was classified based on having an interval of 3 months or less between multiple episodes (15). Medications assessed were nasal drops (use for at least 3 months in 1 year), aspirin (use for at least 3 months in 1 year), balm or peppermint (any use), flower oil (any use), and qufeng oil (any use). Qufeng oil, a traditional Chinese medicine, consists mainly of methyl salicylate, peppermint oil, and camphor oil, and is used topically on the skin to treat arthralgia. For nasal drops and aspirin, additional questions included reasons for use (free text), ages at initiation and cessation of use, frequency of use (times per day, week, or month), and duration of use (years). After data cleaning, 1 case and 17 controls had misplaced data, and 6 controls outside the eligible range at interview were excluded. We further excluded 1 case with missing data on medical history and medication use and 20 cases and 28 controls with poor-quality questionnaire data as determined by the interviewers. After excluding these 73 subjects, 2,532 cases and 2,597 controls were included in the present analysis. Statistical analysis We used multivariate unconditional logistic regression models to estimate odds ratios and corresponding 95% confidence intervals for risk of NPC associated with history of chronic ENT diseases and medication use. In secondary analyses, to reduce the potential for reverse causality, chronic ENT diseases and use of related medications within the 5 years prior to diagnosis (for cases) or interview (for controls) were excluded. Based on prior knowledge and analyses in this study population (3, 4), potential confounders included in the multivariate models were age (in 5-year groups), sex, residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (concrete building, clay brick cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current, former, or never), first-degree family history of NPC (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use (never, yearly, monthly, or weekly or more). Crude differences between NPC cases and controls were compared using the χ2 test for categorical variables and Student’s t test for continuous variables. Where continuous variables were classified into categories, the median value was used as the cutpoint. Data analyses were performed with SAS, version 9.4 (SAS Institute, Inc., Cary, North Carolina). All statistical tests were 2-sided, and a P value of <0.05 was considered statistically significant. RESULTS Descriptive characteristics Table 1 shows the distribution of demographic and other characteristics among the 2,532 NPC cases and 2,597 population-based controls. Because we began interviewing controls about 1 year later than cases, cases were slightly younger than controls. Cases were less educated and more likely to live in cottages, have blue-collar jobs, have a first-degree family history of NPC, have consumed more salt-preserved fish in adulthood, and have used herbal medicines at least weekly, compared with controls. Table 1. Characteristics of Nasopharyngeal Carcinoma Cases and Controls Enrolled in a Population-Based Case-Control Study in Southern China, 2010–2014 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Abbreviation: NPC, nasopharyngeal carcinoma. a Values are expressed as mean (standard deviation). bP value was determined by a 2-sided t test. Other P values were determined by a χ2 test. c Energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake. Table 1. Characteristics of Nasopharyngeal Carcinoma Cases and Controls Enrolled in a Population-Based Case-Control Study in Southern China, 2010–2014 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Abbreviation: NPC, nasopharyngeal carcinoma. a Values are expressed as mean (standard deviation). bP value was determined by a 2-sided t test. Other P values were determined by a χ2 test. c Energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake. ENT diseases Table 2 presents adjusted odds ratios for the association between chronic ENT disease and risk of NPC. Any history of chronic ENT disease was associated with a 34% (95% confidence interval (CI): 12, 59) higher risk of NPC. Having been treated for chronic ENT disease was associated with a similar magnitude of increase in NPC risk. Having been cured of chronic ENT disease was, however, not significantly associated with NPC risk, whereas uncured ENT disease conferred an increased risk (odds ratio (OR) = 1.53, 95% CI: 1.25, 1.89). After exclusion of individuals first diagnosed with ENT disease within the past 5 years, however, odds ratios were attenuated toward (or even past) the null, and none remained statistically significant, except a history of uncured ENT disease (OR = 1.28, 95% CI: 1.00, 1.64) and initial diagnosis of ENT disease at a young age (OR = 1.35, 95% CI: 1.04, 1.76). Table 2. Odds Ratios for Nasopharyngeal Carcinoma Associated With Chronic Ear-Nose-Throat Diseases in Southern China, 2010–2014 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Abbreviations: CI, confidence interval; ENT, ear-nose-throat; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Table 2. Odds Ratios for Nasopharyngeal Carcinoma Associated With Chronic Ear-Nose-Throat Diseases in Southern China, 2010–2014 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Abbreviations: CI, confidence interval; ENT, ear-nose-throat; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Focusing on each chronic ENT disease separately, we found that a history of chronic sinusitis was associated with a 1.3-fold increased risk of NPC, as was treated chronic sinusitis. While cured chronic sinusitis was not significantly associated with NPC risk, uncured chronic sinusitis was positively associated with a close to 50% increased risk of NPC. After restriction of the analysis to those first diagnosed at least 5 years earlier, the associations were generally attenuated and were statistically nonsignificant (Web Table 1, available at https://academic.oup.com/aje). Chronic otitis media was associated with an almost doubled risk of NPC, and the results were similar for treated and uncured chronic otitis media (Web Table 2). Older age at first diagnosis, older age at the most recent occurrence, and persistent chronic otitis media were associated with increased risk of NPC. When we excluded individuals who were first diagnosed within the past 5 years, nearly all estimates were attenuated, and only older age at the most recent diagnosis of chronic otitis media (i.e., having had a more recent occurrence) remained significant (OR = 2.05, 95% CI: 1.06, 3.97). A history of nasal polyps was not significantly associated with NPC risk, but untreated and uncured nasal polyps were associated with significantly greater risk (Web Table 3). When we excluded individuals who were first diagnosed with nasal polyps within the past 5 years, all associations were attenuated and most were statistically nonsignificant, except for untreated nasal polyps (OR = 3.26, 95% CI: 1.14, 9.34). No associations were found between NPC risk and chronic pharyngitis and septal abnormalities, in the primary or secondary analyses (Web Tables 4 and 5). Medications Table 3 shows the adjusted odds ratios for associations between use of nasal drops and risk of NPC. Any history of use of nasal drops was associated with an almost doubled risk of NPC. Use of nasal drops for nasal obstruction demonstrated a significantly increased risk for NPC (OR = 2.82), whereas use of nasal drops for allergic rhinitis did not (OR = 1.23). Older age at initiation and more recent use of nasal drops were more strongly associated with NPC risk than earlier and more distant past use. Shorter duration of nasal drops use (1–6 years), was more strongly associated with NPC risk than longer duration of use (7–40 years), but more frequent use (at least daily) was more strongly associated with risk than less frequent use. However, when individuals who started to use nasal drops within the past 5 years were excluded from the analysis, associations with nasal drops use were weakened, and all were statistically nonsignificant. Table 3. Odds Ratios for Nasopharyngeal Carcinoma Associated With Nasal Drops Use in Southern China, 2010–2014 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Table 3. Odds Ratios for Nasopharyngeal Carcinoma Associated With Nasal Drops Use in Southern China, 2010–2014 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. As shown in Table 4, aspirin use was also associated with an almost doubled risk of NPC. The major reasons for use of aspirin were arthritis and myocardial infarction, neither of which was significantly associated with NPC risk, whereas unspecified “other” reasons for use were associated with significantly greater risk (OR = 2.01). Relative risks did not vary appreciably by age at initiating aspirin, but more distant past use was more strongly associated with NPC risk than more recent use (for last use before age 50 years, OR = 2.58, 95% CI: 1.86, 3.58). Shorter duration of aspirin use (1–5 years) was more strongly associated with NPC risk than longer duration (6–51 years), but more frequent use (at least daily) was associated with greater risk than less frequent use. After restriction of the analysis to those who started using aspirin at least 5 years earlier, aspirin use overall was not significantly associated with NPC risk, but earlier age at initiation and most recent use remained significantly associated with greater NPC risk, although odds ratios were attenuated toward the null (for both, OR = 1.68). Table 4. Odds Ratios for Nasopharyngeal Carcinoma Associated With Aspirin Use in Southern China, 2010–2014 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Table 4. Odds Ratios for Nasopharyngeal Carcinoma Associated With Aspirin Use in Southern China, 2010–2014 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Web Table 6 shows estimated associations with use of balm or peppermint and use of flower or qufeng oil. Both were associated with a significantly elevated risk of NPC (OR = 2.63, 95% CI: 2.00, 3.46, and OR = 2.50, 95% CI: 1.97, 3.18, respectively). Use of both types of herbal medicines was associated with a further increased risk of NPC (OR = 2.95). Because age at first use of these medications was not assessed, individuals who initiated use within the past 5 years could not be excluded from the analysis. DISCUSSION This population-based case-control study, conducted in the NPC-endemic region of southern China, is one of the largest to investigate ENT-related medical history and medication use in the etiology of NPC. A recent history of chronic ENT disease, especially chronic sinusitis and otitis media, was associated with an increased risk of NPC, whereas chronic pharyngitis, nasal polyps, and septal abnormalities had no association with NPC. We also found that having been treated for (but not cured of) chronic ENT disease, chronic sinusitis, or chronic otitis media, or having uncured ENT disease, chronic sinusitis, chronic otitis media, or nasal polyps, was associated with an increased NPC risk. Our results are generally consistent with those from previous studies, including case-control studies in Thailand, Taiwan, the United States, Guangzhou, and Shanghai, China, which reported relative risks from 1.8 to 3.8 in association with a history of overall and specific chronic ENT diseases (7–11, 16, 17). However, after exclusion of individuals first diagnosed with ENT disease within the past 5 years, we found that these associations were substantially weakened and statistically nonsignificant, and only the associations with early age at first diagnosis of ENT disease and untreated nasal polyps remained significant, suggesting an influence of reverse causality or recall bias. The positive associations with treated and uncured ENT disease could be due to greater severity of preclinical disease within 5 years before NPC diagnosis. Nonspecific symptoms of NPC include epistaxis, unilateral nasal obstruction, and auditory complaints due to cranial nerve palsies (18). These symptoms are shared by benign ENT diseases, which should be included in the differential diagnosis for NPC. Although our results are perhaps most likely explained by recall bias or especially reverse causality, where ENT disease is a preclinical symptom of NPC, we could not preclude the possibility of a modest excess risk of NPC associated with ENT disease. A biologically plausible explanation for our findings and those from previous studies, including some that excluded ENT disease within 5 or 10 years of NPC diagnosis (9, 11, 16, 17), is a carcinogenic effect of chronic inflammation. This theory is well supported by epidemiologic evidence on other cancers, as exemplified by the likely association between inflammatory bowel disease and colorectal cancer (19), between Helicobacter pylori infection and gastric cancer (20), and many others (21, 22). However, research on potential inflammatory mechanisms of NPC development remains sparse. With reference to medications for ENT disease, most nasal drops act primarily via vasoconstriction to relieve symptoms of nasal obstruction but not to reduce inflammation. Our study found that a history of nasal drops use within the past 5 years was associated with increased risk of NPC. When individuals who started to use nasal drops within the past 5 years were excluded from the analysis, the association became weaker and statistically nonsignificant. This finding, which may be due to confounding by indication, probably reflects the inflamed condition of the upper respiratory tract before NPC diagnosis. After restriction of the analysis to those who started using aspirin at least 5 years earlier, aspirin use overall was not significantly associated with NPC risk, but earlier age at initiation and more distant past use were significantly associated with greater NPC risk. Aspirin use has been shown to be associated with reduced risk of several common malignancies (23–25). Results of epidemiologic studies analyzing aspirin use and head and neck cancers have been inconsistent (26–28). Thus far, only one small, hospital-based case-control study found a reduced risk of NPC in association with regular aspirin use (13). Although reverse causality must again be considered as a potential explanation for our finding of a positive association between aspirin use and NPC, this result might alternatively be due to the unique involvement of EBV infection, especially EBV reactivation, in the etiology of NPC (29). Given that aspirin can induce EBV activation and lytic cycle replication in EBV-positive cells (30, 31), aspirin might increase NPC risk by reactivating EBV. However, another EBV-associated malignancy, Hodgkin lymphoma, has been shown in some studies to be inversely associated with aspirin use (32, 33). This may be due to the distinctive role of EBV in the pathogenesis of malignancies from epithelial or lymphatic origin. Thus, the potential effect, if any, of aspirin use on NPC development, and whether it might interact with EBV infection, remains uncertain. Given that aspirin use for unspecified reasons other than arthritis and myocardial infarction was most strongly associated with NPC risk, the observed association could have been due to aspirin use for relieving pain, which is a preclinical symptom of NPC. Consistent with the results of a study conducted 4 decades ago in Taiwan, we found that use of balm or peppermint and flower or qufeng oil was associated with increased NPC risk (12), perhaps due to alleviation of potential premonitory symptoms of NPC. However, because we did not collect information about age at first use of these products, we could not conduct a secondary analysis to examine whether the observed positive associations were due to confounding by indication. Our study has some weaknesses. First, all information was retrospective and self-reported. Because NPC cases may overestimate or be more likely than controls to recall their history of chronic ENT diseases and related medication use, especially close to the time of NPC diagnosis, we conducted secondary analyses restricted to chronic ENT diseases and related medication use at least 5 years prior to diagnosis/interview. In general, the magnitude of the associations was attenuated, suggesting an influence of reverse causality and/or recall bias. Second, the lack of blinding of interviewers to case-control status could also have contributed to some amount of information bias. Third, invalid contact information for potential controls might have resulted in some underrepresentation of younger, urban, residentially mobile controls. However, we adjusted for age and socioeconomic factors in the multivariate analysis, and the overall control participation rate was relatively high. Although health-care utilization among enrolled controls might have been lower than in the source population (34), resulting in underascertainment of ENT diseases among controls and overestimation of associations with NPC risk, the attenuation of associations after restriction to diagnoses at least 5 years ago indicates that any such bias was modest. In conclusion, our results indicate that positive association between ENT diseases and NPC risk detected in our study and others is probably due to bias, especially reverse causation resulting from preclinical ENT disease within 5 years of NPC diagnosis. In light of the lack of an association between more distant past ENT disease and NPC risk, our findings call into question any potential role of chronic ENT inflammation in the etiology of NPC. Similarly, the observed associations between the medication use related to ENT diseases and NPC risk might well be due to confounding by indication. However, we could not exclude the possibility of a modest excess NPC risk in association with ENT diseases and their related medication use. Future studies, with particular attention to these pitfalls, are needed to clarify whether there exists a weak association between chronic ENT diseases and/or related medication use, and NPC risk. ACKNOWLEDGMENTS Author affiliations: Department of Otolaryngology–Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, China (Xiling Xiao, Zhe Zhang, Guangwu Huang); Exponent, Inc., Center for Health Sciences, Menlo Park, California (Ellen T. Chang); Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California (Ellen T. Chang); Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland (Zhiwei Liu); Department of Cancer Prevention Center, Sun Yat-sen University Cancer Center, Guangzhou, China (Qing Liu, Shang-Hang Xie, Su-Mei Cao); State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China (Qing Liu, Shang-Hang Xie, Su-Mei Cao, Jian-Yong Shao, Wei-Hua Jia, Yi-Xin Zeng); Department of Clinical Laboratory, Wuzhou Red Cross Hospital, Wuzhou, China (Yonglin Cai, Yuming Zheng); Wuzhou Health System Key Laboratory for Nasopharyngeal Carcinoma Etiology and Molecular Mechanism, Wuzhou, China (Yonglin Cai, Yuming Zheng); State Key Laboratory for Infectious Diseases Prevention and Control, Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China (Guomin Chen, Yi Zeng); Sihui Cancer Institute, Sihui, China (Qi-Hong Huang); Cangwu Institute for Nasopharyngeal Carcinoma Control and Prevention, Wuzhou, China (Jian Liao); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Yufeng Chen, Hans-Olov Adami, Weimin Ye); Key Laboratory of High-Incidence Tumor Prevention and Treatment, Guangxi Medical University, Ministry of Education, Nanning, China (Longde Lin); Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden (Ingemar Ernberg); Beijing Hospital, Beijing, China (Yi-Xin Zeng); and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (Hans-Olov Adami). G.H., Y.Z., Y.-X.Z., H.-O.A., and W.Y. contributed equally to this work. This work was supported by the US National Cancer Institute (grant R01 CA115873), Swedish Research Council (grants 2015-02625, 2015-06268, and 2017-05814), and Karolinska Institutet (Distinguished Professor Award to H.-O.A. (Dnr: 2368/10-221)). The work from the Guiping/Pingnan area was supported by grants from the New Century Excellent Talents in University (grant NCET-12-0654), National Basic Research Program of China (grant 2011CB504300), and Guangxi Natural Science Foundation (grant 2013GXNSFGA 019002). We thank the members of the External Advisory Board, including Drs. Curtis Harris and Allan Hildesheim (National Cancer Institute), Dr. Mary-Claire King (University of Washington), Dr. Xihong Lin (Harvard School of Public Health), Dr. Youlin Qiao (Chinese Academy of Medical Sciences), and Dr. Weicheng You (Peking University Health Science Center). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. Conflict of interest: none declared. Abbreviations CI confidence interval EBV Epstein-Barr virus ENT ear-nose-throat NPC nasopharyngeal carcinoma OR odds ratio REFERENCES 1 Chang ET , Adami HO . The enigmatic epidemiology of nasopharyngeal carcinoma . Cancer Epidemiol Biomarkers Prev . 2006 ; 15 ( 10 ): 1765 – 1777 . Google Scholar Crossref Search ADS PubMed 2 Wu HC , Lin YJ , Lee JJ , et al. . Functional analysis of EBV in nasopharyngeal carcinoma cells . Lab Invest . 2003 ; 83 ( 6 ): 797 – 812 . Google Scholar Crossref Search ADS PubMed 3 Chang ET , Liu Z , Hildesheim A , et al. . Active and passive smoking and risk of nasopharyngeal carcinoma: a population-based case-control study in southern China . Am J Epidemiol . 2017 ; 185 ( 12 ): 1272 – 1280 . Google Scholar Crossref Search ADS PubMed 4 Liu Z , Chang ET , Liu Q , et al. . Oral hygiene and risk of nasopharyngeal carcinoma-a population-based case-control study in China . Cancer Epidemiol Biomarkers Prev . 2016 ; 25 ( 8 ): 1201 – 1207 . Google Scholar Crossref Search ADS PubMed 5 Bei JX , Zuo XY , Liu WS , et al. . Genetic susceptibility to the endemic form of NPC . Chin Clin Oncol . 2016 ; 5 ( 2 ): 15 . Google Scholar Crossref Search ADS PubMed 6 Mantovani A . Cancer: inflaming metastasis . Nature . 2009 ; 457 ( 7225 ): 36 – 37 . Google Scholar Crossref Search ADS PubMed 7 Ekburanawat W , Ekpanyaskul C , Brennan P , et al. . Evaluation of non-viral risk factors for nasopharyngeal carcinoma in Thailand: results from a case-control study . Asian Pac J Cancer Prev . 2010 ; 11 ( 4 ): 929 – 932 . Google Scholar PubMed 8 Henderson BE , Louie E , SooHoo Jing J , et al. . Risk factors associated with nasopharyngeal carcinoma . N Engl J Med . 1976 ; 295 ( 20 ): 1101 – 1106 . Google Scholar Crossref Search ADS PubMed 9 Huang WY , Lin CC , Jen YM , et al. . Association between adult otitis media and nasopharyngeal cancer: a nationwide population-based cohort study . Radiother Oncol . 2012 ; 104 ( 3 ): 338 – 342 . Google Scholar Crossref Search ADS PubMed 10 Hung SH , Chen PY , Lin HC , et al. . Association of rhinosinusitis with nasopharyngeal carcinoma: a population-based study . Laryngoscope . 2014 ; 124 ( 7 ): 1515 – 1520 . Google Scholar Crossref Search ADS PubMed 11 Wu EL , Riley CA , Hsieh MC , et al. . Chronic sinonasal tract inflammation as a precursor to nasopharyngeal carcinoma and sinonasal malignancy in the United States . Int Forum Allergy Rhinol . 2017 ; 7 ( 8 ): 786 – 793 . Google Scholar Crossref Search ADS PubMed 12 Lin TM , Chen KP , Lin CC , et al. . Retrospective study on nasopharyngeal carcinoma . J Natl Cancer Inst . 1973 ; 51 ( 5 ): 1403 – 1408 . Google Scholar Crossref Search ADS PubMed 13 Di Maso M , Bosetti C , La Vecchia C , et al. . Regular aspirin use and nasopharyngeal cancer risk: a case-control study in Italy . Cancer Epidemiol . 2015 ; 39 ( 4 ): 545 – 547 . Google Scholar Crossref Search ADS PubMed 14 Ye W , Chang ET , Liu Z , et al. . Development of a population-based cancer case-control study in southern china . Oncotarget . 2017 ; 8 ( 50 ): 87073 – 87085 . Google Scholar PubMed 15 Sham JS , Wei WI , Lau SK , et al. . Serous otitis media: an opportunity for early recognition of nasopharyngeal carcinoma . Arch Otolaryngol Head Neck Surg . 1992 ; 118 ( 8 ): 794 – 797 . Google Scholar Crossref Search ADS PubMed 16 Yu MC , Garabrant DH , Huang TB , et al. . Occupational and other non‐dietary risk factors for nasopharyngeal carcinoma in Guangzhou, China . Int J Cancer . 1990 ; 45 ( 6 ): 1033 – 1039 . Google Scholar Crossref Search ADS PubMed 17 Yuan JM , Wang XL , Xiang YB , et al. . Non‐dietary risk factors for nasopharyngeal carcinoma in Shanghai, China . Int J Cancer . 2000 ; 85 ( 3 ): 364 – 369 . Google Scholar Crossref Search ADS PubMed 18 Chua MLK , Wee JTS , Hui EP , et al. . Nasopharyngeal carcinoma . Lancet . 2016 ; 387 ( 10022 ): 1012 – 1024 . Google Scholar Crossref Search ADS PubMed 19 Adami HO , Bretthauer M , Emilsson L , et al. . The continuing uncertainty about cancer risk in inflammatory bowel disease . Gut . 2016 ; 65 ( 6 ): 889 – 893 . Google Scholar Crossref Search ADS PubMed 20 Venerito M , Vasapolli R , Rokkas T , et al. . Helicobacter pylori, gastric cancer and other gastrointestinal malignancies . Helicobacter . 2017 ; 22 ( suppl 1 ): e12413 . Google Scholar Crossref Search ADS 21 Wu Y , Antony S , Meitzler JL , et al. . Molecular mechanisms underlying chronic inflammation-associated cancers . Cancer Lett . 2014 ; 345 ( 2 ): 164 – 173 . Google Scholar Crossref Search ADS PubMed 22 Chai EZ , Siveen KS , Shanmugam MK , et al. . Analysis of the intricate relationship between chronic inflammation and cancer . Biochem J . 2015 ; 468 ( 1 ): 1 – 15 . Google Scholar Crossref Search ADS PubMed 23 García Rodríguez LA , Soriano-Gabarró M , Bromley S , et al. . New use of low-dose aspirin and risk of colorectal cancer by stage at diagnosis: a nested case-control study in UK general practice . BMC Cancer . 2017 ; 17 : 637 . Google Scholar Crossref Search ADS PubMed 24 Risch HA , Lu L , Streicher SA , et al. . Aspirin use and reduced risk of pancreatic cancer . Cancer Epidemiol Biomarkers Prev . 2017 ; 26 ( 1 ): 68 – 74 . Google Scholar Crossref Search ADS PubMed 25 Yang YS , Kornelius E , Chiou JY , et al. . Low-dose aspirin reduces breast cancer risk in women with diabetes: a nationwide retrospective cohort study in Taiwan . J Womens Health (Larchmt) . 2017 ; 26 ( 12 ): 1278 – 1284 . Google Scholar Crossref Search ADS PubMed 26 Jayaprakash V , Rigual NR , Moysich KB , et al. . Chemoprevention of head and neck cancer with aspirin: a case-control study . Arch Otolaryngol Head Neck Surg . 2006 ; 132 ( 11 ): 1231 – 1236 . Google Scholar Crossref Search ADS PubMed 27 Macfarlane TV , Lefevre K , Watson MC . Aspirin and non-steroidal anti-inflammatory drug use and the risk of upper aerodigestive tract cancer . Br J Cancer . 2014 ; 111 ( 9 ): 1852 – 1859 . Google Scholar Crossref Search ADS PubMed 28 Rosenquist K , Wennerberg J , Schildt EB , et al. . Oral status, oral infections and some lifestyle factors as risk factors for oral and oropharyngeal squamous cell carcinoma. A population-based case-control study in southern Sweden . Acta Otolaryngol . 2005 ; 125 ( 12 ): 1327 – 1336 . Google Scholar Crossref Search ADS PubMed 29 Chen Y , Zhao W , Lin L , et al. . Nasopharyngeal Epstein-Barr virus load: an efficient supplementary method for population-based nasopharyngeal carcinoma screening . PLoS One . 2015 ; 10 ( 7 ): e0132669 . Google Scholar Crossref Search ADS PubMed 30 Liu SF , Wang H , Li ZJ , et al. . Aspirin induces lytic cytotoxicity in Epstein-Barr virus-positive cells . Eur J Pharmacol . 2008 ; 589 ( 1–3 ): 8 – 13 . Google Scholar Crossref Search ADS PubMed 31 Ordonez P , Nandakumar A , Koriyama C , et al. . Cytotoxic effects of NF-κB inhibitors in combination with anti-herpes agents on Epstein-Barr virus–positive gastric carcinoma in vitro . Mol Med Rep . 2016 ; 14 ( 3 ): 2359 – 2367 . Google Scholar Crossref Search ADS PubMed 32 Chang ET , Cronin-Fenton DP , Friis S , et al. . Aspirin and other nonsteroidal anti-inflammatory drugs in relation to Hodgkin lymphoma risk in northern Denmark . Cancer Epidemiol Biomarkers Prev . 2010 ; 19 ( 1 ): 59 – 64 . Google Scholar Crossref Search ADS PubMed 33 Chang ET , Frøslev T , Sørensen HT , et al. . A nationwide study of aspirin, other non-steroidal anti-inflammatory drugs, and Hodgkin lymphoma risk in Denmark . Br J Cancer . 2011 ; 105 ( 11 ): 1776 – 1782 . Google Scholar Crossref Search ADS PubMed 34 Li J , Shi L , Liang H , et al. . Urban-rural disparities in health care utilization among Chinese adults from 1993 to 2011 . BMC Health Serv Res . 2018 ; 18 : 102 . Google Scholar Crossref Search ADS PubMed Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Epidemiology Oxford University Press

Loading next page...
 
/lp/ou_press/medical-history-medication-use-and-risk-of-nasopharyngeal-carcinoma-S9q0IrD00G
Publisher
Oxford University Press
Copyright
Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2018.
ISSN
0002-9262
eISSN
1476-6256
D.O.I.
10.1093/aje/kwy095
Publisher site
See Article on Publisher Site

Abstract

Abstract Because persistent inflammation may render the nasopharyngeal mucosa susceptible to carcinogenesis, chronic ear-nose-throat (ENT) disease and its treatment might influence the risk of nasopharyngeal carcinoma (NPC). Existing evidence is, however, inconclusive and often based on methodologically suboptimal epidemiologic studies. In a population-based case-control study in southern China, we enrolled 2,532 persons with NPC and 2,597 controls, aged 20–74 years, from 2010 to 2014. Odds ratios were estimated for associations between NPC risk and history of ENT and related medications. Any history of chronic ENT disease was associated with a 34% increased risk of NPC. Similarly, use of nasal drops or aspirin was associated with approximately doubled risk of NPC. However, in secondary analyses restricted to chronic ENT diseases and related medication use at least 5 years prior to diagnosis/interview, most results were statistically nonsignificant, except a history of uncured ENT diseases, untreated nasal polyps, and earlier age at first diagnosis of ENT disease and first or most recent aspirin use. Overall, these findings suggest that ENT disease and related medication use are most likely early indications rather than causes of NPC, although the possibility of a modestly increased NPC risk associated with these diseases and related medications cannot be excluded. case-control study, medical history, medication use, nasopharyngeal carcinoma Nasopharyngeal carcinoma (NPC) has a remarkable geographical and racial/ethnic distribution, and it is endemic in parts of southern China. Numerous studies have suggested that NPC develops through interactions among genetic and environmental factors and Epstein-Barr virus (EBV) infection. The etiologic role of EBV in NPC is supported by molecular analyses, as well as by serological studies (1, 2). Assumed environmental risk factors for NPC include salted fish consumption, smoking, and poor oral health (3, 4), while genetic studies have consistently shown that certain human leukocyte antigens influence NPC risk (5). Inflammation has been proposed as one of the hallmarks of cancer (6), and persistent inflammation and infection of the respiratory tract in particular may render the nasopharyngeal mucosa more susceptible to carcinogenesis. Individual history of ear-nose-throat (ENT) disease, including sinusitis and otitis media, has been shown to increase NPC risk (7–11). Modern medicines, such as aspirin and nasal drops, as well as traditional herbal medicines, such as balms and essential oils, are commonly used in southern China to relieve symptoms of headache and nasal obstruction. Nasal balms or oils may increase NPC risk (12), whereas an inverse association between aspirin use and NPC risk has been reported (13). However, published studies of the use of these medications were either small in size or hospital-based, and observed associations may be due to reverse causality, recall bias, or confounding by underlying ENT disease. To fill the existing knowledge gap regarding the possible relationship of medical history and medication use with NPC risk, we conducted a large, population-based case-control study in southern China, where NPC is endemic. This study enabled a more rigorous investigation of the potential independent etiologic roles of ENT-related medical history and medication use in NPC development. METHODS Study population The NPC Genes, Environment, and EBV study (NPCGEE) is a collaborative population-based case-control study of NPC based in the Zhaoqing area of Guangdong Province and in the Wuzhou and Guiping/Pingnan areas of Guangxi Autonomous Region. These areas encompass 13 cities/counties (Deqing, Fengkai, Gaoyao, Huaiji, Sihui, Zhaoqing, Guangning, Wuzhou, Cenxi, Cangwu, Tengxian, Pingnan, and Guiping) in southern China, with a total population of approximately 8 million. Recruitment of cases and controls was described previously (14). In brief, cases were aged 20–74 years at diagnosis between March 2010 and December 2013, living in the described geographic area, and without a prior history of malignant disease or congenital or acquired immunodeficiency. All cases were histopathologically confirmed by pathology reports. We established a rapid case-ascertainment system including 10 hospitals and 2 cancer research institutions that directly notified study investigators of newly diagnosed NPC cases. In the Zhaoqing area, 1,528 eligible cases were identified between March 2010 and August 2013; in the Wuzhou area, 792 eligible cases were identified between April 2010 and September 2013; in the Guiping/Pingnan area, 727 eligible cases were identified between July 2010 and December 2013. The number of cases identified in each region was close to the expected number of incident NPC cases based on historical incidence rates. Of eligible patients who were contacted by study staff, 1,306 (85% of 1,528 cases) in the Zhaoqing area, 689 (87% of 792 cases) in the Wuzhou area, and 559 (77% of 727 cases) in the Guiping/Pingnan area were enrolled in the study. Controls were randomly selected every 6–12 months between November 2010 and November 2014 from continuously updated total population registries covering the Zhaoqing, Wuzhou, and Guiping/Pingnan populations, with frequency matching to the 5-year-age and sex distribution of the cases according to geographic region. Eligible controls were required to be residents of the study area without a prior history of malignant disease or congenital or acquired immune deficiency. Controls who had worked outside of the study area for 10 years or more, as identified with the help of the local government in each town or community, were not considered part of the study base, because they were highly unlikely to return to the study area if they were diagnosed with NPC; therefore, they were replaced. Of 3,932 potential controls selected from the total population registries, 730 (19%) could not be linked to an identifiable person because of invalid contact information. Of the 3,202 who were identified, 138 (4%) had emigrated out of the study area, 90 (3%) were deceased or incapacitated, and 326 (10%) refused to participate. Of the 2,648 (83% of 3,202) enrolled controls, 2,133 (81%) were initial selections from the population registry, and the other 515 (19%) were replacements. This study was approved by the institutional review boards of Sun Yat-sen University Cancer Center, the Institute for Viral Disease Control and Prevention of the Chinese Center for Disease Control and Prevention, Guangxi Medical University, and Harvard T.H. Chan School of Public Health, as well as the Regional Research Ethics Vetting Board in Stockholm, Sweden. All subjects granted written or oral informed consent to participate. Data collection Trained interviewers used a structured electronic questionnaire to conduct audiotaped face-to-face or telephone interviews with study participants. Although blinding to case-control status was not feasible, in an effort to reduce information bias, we required all interviewers, who were unaware of the study hypotheses, to interview an approximately equal number of cases and controls. The questionnaire covered demographic characteristics, residential history, occupational history, medical history of chronic ENT disease, medication use, family medical history, dietary habits, cigarette smoking, alcohol and tea drinking, and use of Chinese herbal medicine, among other topics. Questionnaire data were automatically flagged for logic errors and missing values, and errors were corrected by making comparisons against audio recordings or by contacting participants again. Five chronic ENT diseases were investigated: chronic sinusitis, chronic pharyngitis, chronic otitis media, nasal polyps, and septal abnormalities. For each disease, questions addressed whether the subject had ever been diagnosed (yes or no), age at diagnosis, number of times of diagnosed, age at most recent occurrence, any use of medications or surgical treatment, and whether the disease had been cured (i.e., was no longer symptomatic). Persistent, chronic ENT disease was classified based on having an interval of 3 months or less between multiple episodes (15). Medications assessed were nasal drops (use for at least 3 months in 1 year), aspirin (use for at least 3 months in 1 year), balm or peppermint (any use), flower oil (any use), and qufeng oil (any use). Qufeng oil, a traditional Chinese medicine, consists mainly of methyl salicylate, peppermint oil, and camphor oil, and is used topically on the skin to treat arthralgia. For nasal drops and aspirin, additional questions included reasons for use (free text), ages at initiation and cessation of use, frequency of use (times per day, week, or month), and duration of use (years). After data cleaning, 1 case and 17 controls had misplaced data, and 6 controls outside the eligible range at interview were excluded. We further excluded 1 case with missing data on medical history and medication use and 20 cases and 28 controls with poor-quality questionnaire data as determined by the interviewers. After excluding these 73 subjects, 2,532 cases and 2,597 controls were included in the present analysis. Statistical analysis We used multivariate unconditional logistic regression models to estimate odds ratios and corresponding 95% confidence intervals for risk of NPC associated with history of chronic ENT diseases and medication use. In secondary analyses, to reduce the potential for reverse causality, chronic ENT diseases and use of related medications within the 5 years prior to diagnosis (for cases) or interview (for controls) were excluded. Based on prior knowledge and analyses in this study population (3, 4), potential confounders included in the multivariate models were age (in 5-year groups), sex, residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (concrete building, clay brick cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current, former, or never), first-degree family history of NPC (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use (never, yearly, monthly, or weekly or more). Crude differences between NPC cases and controls were compared using the χ2 test for categorical variables and Student’s t test for continuous variables. Where continuous variables were classified into categories, the median value was used as the cutpoint. Data analyses were performed with SAS, version 9.4 (SAS Institute, Inc., Cary, North Carolina). All statistical tests were 2-sided, and a P value of <0.05 was considered statistically significant. RESULTS Descriptive characteristics Table 1 shows the distribution of demographic and other characteristics among the 2,532 NPC cases and 2,597 population-based controls. Because we began interviewing controls about 1 year later than cases, cases were slightly younger than controls. Cases were less educated and more likely to live in cottages, have blue-collar jobs, have a first-degree family history of NPC, have consumed more salt-preserved fish in adulthood, and have used herbal medicines at least weekly, compared with controls. Table 1. Characteristics of Nasopharyngeal Carcinoma Cases and Controls Enrolled in a Population-Based Case-Control Study in Southern China, 2010–2014 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Abbreviation: NPC, nasopharyngeal carcinoma. a Values are expressed as mean (standard deviation). bP value was determined by a 2-sided t test. Other P values were determined by a χ2 test. c Energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake. Table 1. Characteristics of Nasopharyngeal Carcinoma Cases and Controls Enrolled in a Population-Based Case-Control Study in Southern China, 2010–2014 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Characteristic Case Group (n = 2,532) Control Group (n = 2,597) P Value No. % No. % Residential area 0.3  Zhaoqing 1,286 50.8 1,321 50.9  Wuzhou 688 27.2 665 25.6  Guiping/Pingnan 558 22.0 611 23.5 Sex 0.97  Male 1,860 73.5 1,909 73.5  Female 672 26.5 688 26.5 Age at diagnosis/interview, years  Overalla 48.54 (10.70) 49.75 (10.90) <0.001b  20–34 232 9.2 207 8.1 0.07  35–39 277 11.0 246 9.5  40–44 418 16.5 399 15.4  45–49 492 19.4 491 18.9  50–54 333 13.2 347 13.4  55–59 353 13.9 382 14.7  60–74 427 16.9 525 20.2 Educational level, years 0.004  ≤6 1,005 39.7 932 35.9  7–9 1,013 40.0 1,040 40.1  10–12 407 16.1 484 18.6  >12 107 4.2 141 5.4 Current housing type <0.001  Building (concrete structure) 1,820 71.9 2,019 77.7  Cottage (clay brick structure) 702 27.7 575 22.1  Boat 10 0.4 2 0.1  Missing 0 0 1 0.04 Current occupation <0.001  Unemployed 78 3.1 96 3.7  Farmer 855 33.8 984 37.9  Blue-collar 1,023 40.4 900 34.7  White-collar 350 13.8 416 16.0  Other/unknown 226 8.9 201 7.7 Cigarette smoking 0.12  Current smoker 1,121 44.3 1,213 46.7  Former smoker 182 7.2 152 5.9  Never smoker 1,228 48.5 1,230 47.4  Missing 1 0.04 2 0.1 First-degree family history of NPC <0.001  No 2,208 87.2 2,483 95.6  Yes 272 10.7 70 2.7  Unknown 46 1.8 43 1.7  Missing 6 0.2 1 0.04 Alcohol drinking 0.11  Never 1,735 68.5 1,815 69.9  Ever 791 31.2 766 29.5  Missing 6 0.2 16 0.6 Tea drinking <0.001  Never 1,618 63.8 1,513 58.3  Ever 911 36.0 1,081 41.6  Missing 3 0.1 3 0.1 Salt-preserved fish consumption in adult diet, categoryc <0.001  1 846 33.4 797 30.7  2 489 19.3 583 22.5  3 488 19.3 582 22.4  4 678 26.8 596 23.0  Missing 31 1.2 39 1.5 Herbal medicine use 0.03  Nonusers 355 14.0 419 16.1  Yearly 965 38.1 974 37.5  Monthly 905 35.7 942 36.3  Weekly or more often 269 10.6 220 8.5  Missing 38 1.5 42 1.6 Abbreviation: NPC, nasopharyngeal carcinoma. a Values are expressed as mean (standard deviation). bP value was determined by a 2-sided t test. Other P values were determined by a χ2 test. c Energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake. ENT diseases Table 2 presents adjusted odds ratios for the association between chronic ENT disease and risk of NPC. Any history of chronic ENT disease was associated with a 34% (95% confidence interval (CI): 12, 59) higher risk of NPC. Having been treated for chronic ENT disease was associated with a similar magnitude of increase in NPC risk. Having been cured of chronic ENT disease was, however, not significantly associated with NPC risk, whereas uncured ENT disease conferred an increased risk (odds ratio (OR) = 1.53, 95% CI: 1.25, 1.89). After exclusion of individuals first diagnosed with ENT disease within the past 5 years, however, odds ratios were attenuated toward (or even past) the null, and none remained statistically significant, except a history of uncured ENT disease (OR = 1.28, 95% CI: 1.00, 1.64) and initial diagnosis of ENT disease at a young age (OR = 1.35, 95% CI: 1.04, 1.76). Table 2. Odds Ratios for Nasopharyngeal Carcinoma Associated With Chronic Ear-Nose-Throat Diseases in Southern China, 2010–2014 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Abbreviations: CI, confidence interval; ENT, ear-nose-throat; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Table 2. Odds Ratios for Nasopharyngeal Carcinoma Associated With Chronic Ear-Nose-Throat Diseases in Southern China, 2010–2014 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Variable Any History of Chronic ENT Disease ENT Disease Diagnosed More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,413) No. of Controls (n = 2,533) ORa 95% CIa Chronic ENT diseases  No 2,161 2,304 1.00 Referent 2,161 2,304 1.00 Referent  Yes 371 293 1.34 1.12, 1.59 240 223 1.16 0.94, 1.42   Untreated 61 52 1.29 0.87, 1.92 36 42 0.96 0.60, 1.54   Some diseases treated 310 241 1.35 1.12, 1.63 216 187 1.23 0.99, 1.53   Uncured 260 183 1.53 1.25, 1.89 167 141 1.28 1.00, 1.64   Some diseases cured 111 110 1.01 0.76, 1.35 85 88 1.02 0.73, 1.40  Missing 0 0 12 6  Age at first diagnosis, years   1–30 181 140 1.39 1.09, 1.77 151 118 1.35 1.04, 1.76   31–74 178 147 1.26 1.00, 1.60 89 105 0.94 0.69, 1.27   Unknown 12 6 12 6 Abbreviations: CI, confidence interval; ENT, ear-nose-throat; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Focusing on each chronic ENT disease separately, we found that a history of chronic sinusitis was associated with a 1.3-fold increased risk of NPC, as was treated chronic sinusitis. While cured chronic sinusitis was not significantly associated with NPC risk, uncured chronic sinusitis was positively associated with a close to 50% increased risk of NPC. After restriction of the analysis to those first diagnosed at least 5 years earlier, the associations were generally attenuated and were statistically nonsignificant (Web Table 1, available at https://academic.oup.com/aje). Chronic otitis media was associated with an almost doubled risk of NPC, and the results were similar for treated and uncured chronic otitis media (Web Table 2). Older age at first diagnosis, older age at the most recent occurrence, and persistent chronic otitis media were associated with increased risk of NPC. When we excluded individuals who were first diagnosed within the past 5 years, nearly all estimates were attenuated, and only older age at the most recent diagnosis of chronic otitis media (i.e., having had a more recent occurrence) remained significant (OR = 2.05, 95% CI: 1.06, 3.97). A history of nasal polyps was not significantly associated with NPC risk, but untreated and uncured nasal polyps were associated with significantly greater risk (Web Table 3). When we excluded individuals who were first diagnosed with nasal polyps within the past 5 years, all associations were attenuated and most were statistically nonsignificant, except for untreated nasal polyps (OR = 3.26, 95% CI: 1.14, 9.34). No associations were found between NPC risk and chronic pharyngitis and septal abnormalities, in the primary or secondary analyses (Web Tables 4 and 5). Medications Table 3 shows the adjusted odds ratios for associations between use of nasal drops and risk of NPC. Any history of use of nasal drops was associated with an almost doubled risk of NPC. Use of nasal drops for nasal obstruction demonstrated a significantly increased risk for NPC (OR = 2.82), whereas use of nasal drops for allergic rhinitis did not (OR = 1.23). Older age at initiation and more recent use of nasal drops were more strongly associated with NPC risk than earlier and more distant past use. Shorter duration of nasal drops use (1–6 years), was more strongly associated with NPC risk than longer duration of use (7–40 years), but more frequent use (at least daily) was more strongly associated with risk than less frequent use. However, when individuals who started to use nasal drops within the past 5 years were excluded from the analysis, associations with nasal drops use were weakened, and all were statistically nonsignificant. Table 3. Odds Ratios for Nasopharyngeal Carcinoma Associated With Nasal Drops Use in Southern China, 2010–2014 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Table 3. Odds Ratios for Nasopharyngeal Carcinoma Associated With Nasal Drops Use in Southern China, 2010–2014 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Variable Any History of Nasal Drops First Use of Nasal Drops More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,497) No. of Controls (n = 2,590) ORa 95% CIa History of nasal drops use (at least 3 months in 1 year)  No 2,458 2,558 1.00 Referent 2,458 2,558 1.00 Referent  Yes 74 39 1.98 1.31, 3.01 39 32 1.25 0.75, 2.07 Reason for use of nasal drops  Nasal obstruction 51 20 2.82 1.63, 4.88 25 15 1.80 0.90, 3.59  Allergic rhinitis 13 10 1.23 0.50, 3.00 12 9 1.39 0.54, 3.55  Other 10 9 1.06 0.41, 2.73 2 8 0.24 0.05, 1.15 Age at first use of nasal drops, years  1–34 32 20 1.69 0.92, 3.09 20 17 1.30 0.64, 2.65  35–64 42 19 2.28 1.29, 4.02 19 15 1.20 0.58, 2.44 Age at most recent use of nasal drops, years  1–42 32 19 1.68 0.92, 3.07 21 16 1.34 0.67, 2.68  43–74 42 20 2.29 1.30, 4.05 18 16 1.16 0.56, 2.41 Duration of nasal drops use, years  1–6 52 21 2.55 1.51, 4.31 21 16 1.31 0.67, 2.57  7–40 22 18 1.23 0.61, 2.48 18 16 1.17 0.55, 2.51 No. of uses of nasal drops  ≥1/day 39 15 2.51 1.35, 4.65 21 13 1.48 0.72, 3.06  ≥1/week 15 12 1.38 0.60, 3.17 7 11 0.70 0.25, 2.02  ≥1/month 19 12 1.84 0.83, 3.92 11 8 1.54 0.57, 4.16  Missing 1 0 0 0 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. As shown in Table 4, aspirin use was also associated with an almost doubled risk of NPC. The major reasons for use of aspirin were arthritis and myocardial infarction, neither of which was significantly associated with NPC risk, whereas unspecified “other” reasons for use were associated with significantly greater risk (OR = 2.01). Relative risks did not vary appreciably by age at initiating aspirin, but more distant past use was more strongly associated with NPC risk than more recent use (for last use before age 50 years, OR = 2.58, 95% CI: 1.86, 3.58). Shorter duration of aspirin use (1–5 years) was more strongly associated with NPC risk than longer duration (6–51 years), but more frequent use (at least daily) was associated with greater risk than less frequent use. After restriction of the analysis to those who started using aspirin at least 5 years earlier, aspirin use overall was not significantly associated with NPC risk, but earlier age at initiation and most recent use remained significantly associated with greater NPC risk, although odds ratios were attenuated toward the null (for both, OR = 1.68). Table 4. Odds Ratios for Nasopharyngeal Carcinoma Associated With Aspirin Use in Southern China, 2010–2014 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Table 4. Odds Ratios for Nasopharyngeal Carcinoma Associated With Aspirin Use in Southern China, 2010–2014 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Variable Aspirin Use First Use of Aspirin More Than 5 Years Before Interview No. of Cases (n = 2,532) No. of Controls (n = 2,597) ORa 95% CIa No. of Cases (n = 2,390) No. of Controls (n = 2,551) ORa 95% CIa History of aspirin use (at least 3 months in 1 year)  No 2,291 2,468 1.00 Referent 2,291 2,468 1.00 Referent  Yes 241 129 1.91 1.52, 2.41 99 83 1.21 0.89, 1.66 Reason for use of aspirin  Arthritis 16 15 1.37 0.66, 2.87 11 9 1.39 0.56, 3.46  Myocardial infarction 0 2 0 2  Other 225 112 2.01 1.57, 2.57 88 72 1.22 0.88, 1.71 Age at first use of aspirin, years  1–40 130 63 2.05 1.49, 2.83 72 43 1.68 1.13, 2.52  41–74 111 66 1.77 1.28, 2.46 27 40 0.69 0.41, 1.17 Age at most recent use of aspirin, years  16–49 147 55 2.58 1.86, 3.58 63 35 1.68 1.08, 2.60  50–74 94 74 1.38 0.99, 1.92 36 48 0.85 0.53, 1.34 Duration of aspirin use, years  1–5 158 64 2.43 1.79, 3.31 33 35 0.87 0.53, 1.45  6–51 83 65 1.38 0.98, 1.95 66 48 1.48 0.99, 2.20 No. of uses of aspirin  ≥1/day 89 34 2.54 1.67, 3.85 23 18 1.28 0.66, 2.48  ≥1/week 35 20 1.67 0.94, 2.96 12 9 1.09 0.43, 2.74  ≥1/month 116 73 1.72 1.26, 2.35 63 54 1.24 0.84, 1.82  Missing 1 2 1 2 Abbreviations: CI, confidence interval; OR, odds ratio. a Adjusted for sex, age (5-year categories), residential area (Zhaoqing, Wuzhou, or Guiping/Pingnan), educational level (in years: ≤6, 7–9, 10–12, or >12), current housing type (building, cottage, or boat), current occupation (unemployed, farmer, blue-collar, white-collar, or other/unknown), cigarette smoking (current smoker, former smoker, or never smoker), first-degree family history of nasopharyngeal carcinoma (yes, no, or unknown), alcohol drinking (never, ever), tea drinking (never, ever), salt-preserved fish consumption in adulthood (energy-adjusted intake categories: 1 = lowest intake (none) to 4 = highest intake), and herbal medicine use. Web Table 6 shows estimated associations with use of balm or peppermint and use of flower or qufeng oil. Both were associated with a significantly elevated risk of NPC (OR = 2.63, 95% CI: 2.00, 3.46, and OR = 2.50, 95% CI: 1.97, 3.18, respectively). Use of both types of herbal medicines was associated with a further increased risk of NPC (OR = 2.95). Because age at first use of these medications was not assessed, individuals who initiated use within the past 5 years could not be excluded from the analysis. DISCUSSION This population-based case-control study, conducted in the NPC-endemic region of southern China, is one of the largest to investigate ENT-related medical history and medication use in the etiology of NPC. A recent history of chronic ENT disease, especially chronic sinusitis and otitis media, was associated with an increased risk of NPC, whereas chronic pharyngitis, nasal polyps, and septal abnormalities had no association with NPC. We also found that having been treated for (but not cured of) chronic ENT disease, chronic sinusitis, or chronic otitis media, or having uncured ENT disease, chronic sinusitis, chronic otitis media, or nasal polyps, was associated with an increased NPC risk. Our results are generally consistent with those from previous studies, including case-control studies in Thailand, Taiwan, the United States, Guangzhou, and Shanghai, China, which reported relative risks from 1.8 to 3.8 in association with a history of overall and specific chronic ENT diseases (7–11, 16, 17). However, after exclusion of individuals first diagnosed with ENT disease within the past 5 years, we found that these associations were substantially weakened and statistically nonsignificant, and only the associations with early age at first diagnosis of ENT disease and untreated nasal polyps remained significant, suggesting an influence of reverse causality or recall bias. The positive associations with treated and uncured ENT disease could be due to greater severity of preclinical disease within 5 years before NPC diagnosis. Nonspecific symptoms of NPC include epistaxis, unilateral nasal obstruction, and auditory complaints due to cranial nerve palsies (18). These symptoms are shared by benign ENT diseases, which should be included in the differential diagnosis for NPC. Although our results are perhaps most likely explained by recall bias or especially reverse causality, where ENT disease is a preclinical symptom of NPC, we could not preclude the possibility of a modest excess risk of NPC associated with ENT disease. A biologically plausible explanation for our findings and those from previous studies, including some that excluded ENT disease within 5 or 10 years of NPC diagnosis (9, 11, 16, 17), is a carcinogenic effect of chronic inflammation. This theory is well supported by epidemiologic evidence on other cancers, as exemplified by the likely association between inflammatory bowel disease and colorectal cancer (19), between Helicobacter pylori infection and gastric cancer (20), and many others (21, 22). However, research on potential inflammatory mechanisms of NPC development remains sparse. With reference to medications for ENT disease, most nasal drops act primarily via vasoconstriction to relieve symptoms of nasal obstruction but not to reduce inflammation. Our study found that a history of nasal drops use within the past 5 years was associated with increased risk of NPC. When individuals who started to use nasal drops within the past 5 years were excluded from the analysis, the association became weaker and statistically nonsignificant. This finding, which may be due to confounding by indication, probably reflects the inflamed condition of the upper respiratory tract before NPC diagnosis. After restriction of the analysis to those who started using aspirin at least 5 years earlier, aspirin use overall was not significantly associated with NPC risk, but earlier age at initiation and more distant past use were significantly associated with greater NPC risk. Aspirin use has been shown to be associated with reduced risk of several common malignancies (23–25). Results of epidemiologic studies analyzing aspirin use and head and neck cancers have been inconsistent (26–28). Thus far, only one small, hospital-based case-control study found a reduced risk of NPC in association with regular aspirin use (13). Although reverse causality must again be considered as a potential explanation for our finding of a positive association between aspirin use and NPC, this result might alternatively be due to the unique involvement of EBV infection, especially EBV reactivation, in the etiology of NPC (29). Given that aspirin can induce EBV activation and lytic cycle replication in EBV-positive cells (30, 31), aspirin might increase NPC risk by reactivating EBV. However, another EBV-associated malignancy, Hodgkin lymphoma, has been shown in some studies to be inversely associated with aspirin use (32, 33). This may be due to the distinctive role of EBV in the pathogenesis of malignancies from epithelial or lymphatic origin. Thus, the potential effect, if any, of aspirin use on NPC development, and whether it might interact with EBV infection, remains uncertain. Given that aspirin use for unspecified reasons other than arthritis and myocardial infarction was most strongly associated with NPC risk, the observed association could have been due to aspirin use for relieving pain, which is a preclinical symptom of NPC. Consistent with the results of a study conducted 4 decades ago in Taiwan, we found that use of balm or peppermint and flower or qufeng oil was associated with increased NPC risk (12), perhaps due to alleviation of potential premonitory symptoms of NPC. However, because we did not collect information about age at first use of these products, we could not conduct a secondary analysis to examine whether the observed positive associations were due to confounding by indication. Our study has some weaknesses. First, all information was retrospective and self-reported. Because NPC cases may overestimate or be more likely than controls to recall their history of chronic ENT diseases and related medication use, especially close to the time of NPC diagnosis, we conducted secondary analyses restricted to chronic ENT diseases and related medication use at least 5 years prior to diagnosis/interview. In general, the magnitude of the associations was attenuated, suggesting an influence of reverse causality and/or recall bias. Second, the lack of blinding of interviewers to case-control status could also have contributed to some amount of information bias. Third, invalid contact information for potential controls might have resulted in some underrepresentation of younger, urban, residentially mobile controls. However, we adjusted for age and socioeconomic factors in the multivariate analysis, and the overall control participation rate was relatively high. Although health-care utilization among enrolled controls might have been lower than in the source population (34), resulting in underascertainment of ENT diseases among controls and overestimation of associations with NPC risk, the attenuation of associations after restriction to diagnoses at least 5 years ago indicates that any such bias was modest. In conclusion, our results indicate that positive association between ENT diseases and NPC risk detected in our study and others is probably due to bias, especially reverse causation resulting from preclinical ENT disease within 5 years of NPC diagnosis. In light of the lack of an association between more distant past ENT disease and NPC risk, our findings call into question any potential role of chronic ENT inflammation in the etiology of NPC. Similarly, the observed associations between the medication use related to ENT diseases and NPC risk might well be due to confounding by indication. However, we could not exclude the possibility of a modest excess NPC risk in association with ENT diseases and their related medication use. Future studies, with particular attention to these pitfalls, are needed to clarify whether there exists a weak association between chronic ENT diseases and/or related medication use, and NPC risk. ACKNOWLEDGMENTS Author affiliations: Department of Otolaryngology–Head and Neck Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, China (Xiling Xiao, Zhe Zhang, Guangwu Huang); Exponent, Inc., Center for Health Sciences, Menlo Park, California (Ellen T. Chang); Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California (Ellen T. Chang); Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland (Zhiwei Liu); Department of Cancer Prevention Center, Sun Yat-sen University Cancer Center, Guangzhou, China (Qing Liu, Shang-Hang Xie, Su-Mei Cao); State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China (Qing Liu, Shang-Hang Xie, Su-Mei Cao, Jian-Yong Shao, Wei-Hua Jia, Yi-Xin Zeng); Department of Clinical Laboratory, Wuzhou Red Cross Hospital, Wuzhou, China (Yonglin Cai, Yuming Zheng); Wuzhou Health System Key Laboratory for Nasopharyngeal Carcinoma Etiology and Molecular Mechanism, Wuzhou, China (Yonglin Cai, Yuming Zheng); State Key Laboratory for Infectious Diseases Prevention and Control, Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China (Guomin Chen, Yi Zeng); Sihui Cancer Institute, Sihui, China (Qi-Hong Huang); Cangwu Institute for Nasopharyngeal Carcinoma Control and Prevention, Wuzhou, China (Jian Liao); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Yufeng Chen, Hans-Olov Adami, Weimin Ye); Key Laboratory of High-Incidence Tumor Prevention and Treatment, Guangxi Medical University, Ministry of Education, Nanning, China (Longde Lin); Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden (Ingemar Ernberg); Beijing Hospital, Beijing, China (Yi-Xin Zeng); and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (Hans-Olov Adami). G.H., Y.Z., Y.-X.Z., H.-O.A., and W.Y. contributed equally to this work. This work was supported by the US National Cancer Institute (grant R01 CA115873), Swedish Research Council (grants 2015-02625, 2015-06268, and 2017-05814), and Karolinska Institutet (Distinguished Professor Award to H.-O.A. (Dnr: 2368/10-221)). The work from the Guiping/Pingnan area was supported by grants from the New Century Excellent Talents in University (grant NCET-12-0654), National Basic Research Program of China (grant 2011CB504300), and Guangxi Natural Science Foundation (grant 2013GXNSFGA 019002). We thank the members of the External Advisory Board, including Drs. Curtis Harris and Allan Hildesheim (National Cancer Institute), Dr. Mary-Claire King (University of Washington), Dr. Xihong Lin (Harvard School of Public Health), Dr. Youlin Qiao (Chinese Academy of Medical Sciences), and Dr. Weicheng You (Peking University Health Science Center). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. Conflict of interest: none declared. Abbreviations CI confidence interval EBV Epstein-Barr virus ENT ear-nose-throat NPC nasopharyngeal carcinoma OR odds ratio REFERENCES 1 Chang ET , Adami HO . The enigmatic epidemiology of nasopharyngeal carcinoma . Cancer Epidemiol Biomarkers Prev . 2006 ; 15 ( 10 ): 1765 – 1777 . Google Scholar Crossref Search ADS PubMed 2 Wu HC , Lin YJ , Lee JJ , et al. . Functional analysis of EBV in nasopharyngeal carcinoma cells . Lab Invest . 2003 ; 83 ( 6 ): 797 – 812 . Google Scholar Crossref Search ADS PubMed 3 Chang ET , Liu Z , Hildesheim A , et al. . Active and passive smoking and risk of nasopharyngeal carcinoma: a population-based case-control study in southern China . Am J Epidemiol . 2017 ; 185 ( 12 ): 1272 – 1280 . Google Scholar Crossref Search ADS PubMed 4 Liu Z , Chang ET , Liu Q , et al. . Oral hygiene and risk of nasopharyngeal carcinoma-a population-based case-control study in China . Cancer Epidemiol Biomarkers Prev . 2016 ; 25 ( 8 ): 1201 – 1207 . Google Scholar Crossref Search ADS PubMed 5 Bei JX , Zuo XY , Liu WS , et al. . Genetic susceptibility to the endemic form of NPC . Chin Clin Oncol . 2016 ; 5 ( 2 ): 15 . Google Scholar Crossref Search ADS PubMed 6 Mantovani A . Cancer: inflaming metastasis . Nature . 2009 ; 457 ( 7225 ): 36 – 37 . Google Scholar Crossref Search ADS PubMed 7 Ekburanawat W , Ekpanyaskul C , Brennan P , et al. . Evaluation of non-viral risk factors for nasopharyngeal carcinoma in Thailand: results from a case-control study . Asian Pac J Cancer Prev . 2010 ; 11 ( 4 ): 929 – 932 . Google Scholar PubMed 8 Henderson BE , Louie E , SooHoo Jing J , et al. . Risk factors associated with nasopharyngeal carcinoma . N Engl J Med . 1976 ; 295 ( 20 ): 1101 – 1106 . Google Scholar Crossref Search ADS PubMed 9 Huang WY , Lin CC , Jen YM , et al. . Association between adult otitis media and nasopharyngeal cancer: a nationwide population-based cohort study . Radiother Oncol . 2012 ; 104 ( 3 ): 338 – 342 . Google Scholar Crossref Search ADS PubMed 10 Hung SH , Chen PY , Lin HC , et al. . Association of rhinosinusitis with nasopharyngeal carcinoma: a population-based study . Laryngoscope . 2014 ; 124 ( 7 ): 1515 – 1520 . Google Scholar Crossref Search ADS PubMed 11 Wu EL , Riley CA , Hsieh MC , et al. . Chronic sinonasal tract inflammation as a precursor to nasopharyngeal carcinoma and sinonasal malignancy in the United States . Int Forum Allergy Rhinol . 2017 ; 7 ( 8 ): 786 – 793 . Google Scholar Crossref Search ADS PubMed 12 Lin TM , Chen KP , Lin CC , et al. . Retrospective study on nasopharyngeal carcinoma . J Natl Cancer Inst . 1973 ; 51 ( 5 ): 1403 – 1408 . Google Scholar Crossref Search ADS PubMed 13 Di Maso M , Bosetti C , La Vecchia C , et al. . Regular aspirin use and nasopharyngeal cancer risk: a case-control study in Italy . Cancer Epidemiol . 2015 ; 39 ( 4 ): 545 – 547 . Google Scholar Crossref Search ADS PubMed 14 Ye W , Chang ET , Liu Z , et al. . Development of a population-based cancer case-control study in southern china . Oncotarget . 2017 ; 8 ( 50 ): 87073 – 87085 . Google Scholar PubMed 15 Sham JS , Wei WI , Lau SK , et al. . Serous otitis media: an opportunity for early recognition of nasopharyngeal carcinoma . Arch Otolaryngol Head Neck Surg . 1992 ; 118 ( 8 ): 794 – 797 . Google Scholar Crossref Search ADS PubMed 16 Yu MC , Garabrant DH , Huang TB , et al. . Occupational and other non‐dietary risk factors for nasopharyngeal carcinoma in Guangzhou, China . Int J Cancer . 1990 ; 45 ( 6 ): 1033 – 1039 . Google Scholar Crossref Search ADS PubMed 17 Yuan JM , Wang XL , Xiang YB , et al. . Non‐dietary risk factors for nasopharyngeal carcinoma in Shanghai, China . Int J Cancer . 2000 ; 85 ( 3 ): 364 – 369 . Google Scholar Crossref Search ADS PubMed 18 Chua MLK , Wee JTS , Hui EP , et al. . Nasopharyngeal carcinoma . Lancet . 2016 ; 387 ( 10022 ): 1012 – 1024 . Google Scholar Crossref Search ADS PubMed 19 Adami HO , Bretthauer M , Emilsson L , et al. . The continuing uncertainty about cancer risk in inflammatory bowel disease . Gut . 2016 ; 65 ( 6 ): 889 – 893 . Google Scholar Crossref Search ADS PubMed 20 Venerito M , Vasapolli R , Rokkas T , et al. . Helicobacter pylori, gastric cancer and other gastrointestinal malignancies . Helicobacter . 2017 ; 22 ( suppl 1 ): e12413 . Google Scholar Crossref Search ADS 21 Wu Y , Antony S , Meitzler JL , et al. . Molecular mechanisms underlying chronic inflammation-associated cancers . Cancer Lett . 2014 ; 345 ( 2 ): 164 – 173 . Google Scholar Crossref Search ADS PubMed 22 Chai EZ , Siveen KS , Shanmugam MK , et al. . Analysis of the intricate relationship between chronic inflammation and cancer . Biochem J . 2015 ; 468 ( 1 ): 1 – 15 . Google Scholar Crossref Search ADS PubMed 23 García Rodríguez LA , Soriano-Gabarró M , Bromley S , et al. . New use of low-dose aspirin and risk of colorectal cancer by stage at diagnosis: a nested case-control study in UK general practice . BMC Cancer . 2017 ; 17 : 637 . Google Scholar Crossref Search ADS PubMed 24 Risch HA , Lu L , Streicher SA , et al. . Aspirin use and reduced risk of pancreatic cancer . Cancer Epidemiol Biomarkers Prev . 2017 ; 26 ( 1 ): 68 – 74 . Google Scholar Crossref Search ADS PubMed 25 Yang YS , Kornelius E , Chiou JY , et al. . Low-dose aspirin reduces breast cancer risk in women with diabetes: a nationwide retrospective cohort study in Taiwan . J Womens Health (Larchmt) . 2017 ; 26 ( 12 ): 1278 – 1284 . Google Scholar Crossref Search ADS PubMed 26 Jayaprakash V , Rigual NR , Moysich KB , et al. . Chemoprevention of head and neck cancer with aspirin: a case-control study . Arch Otolaryngol Head Neck Surg . 2006 ; 132 ( 11 ): 1231 – 1236 . Google Scholar Crossref Search ADS PubMed 27 Macfarlane TV , Lefevre K , Watson MC . Aspirin and non-steroidal anti-inflammatory drug use and the risk of upper aerodigestive tract cancer . Br J Cancer . 2014 ; 111 ( 9 ): 1852 – 1859 . Google Scholar Crossref Search ADS PubMed 28 Rosenquist K , Wennerberg J , Schildt EB , et al. . Oral status, oral infections and some lifestyle factors as risk factors for oral and oropharyngeal squamous cell carcinoma. A population-based case-control study in southern Sweden . Acta Otolaryngol . 2005 ; 125 ( 12 ): 1327 – 1336 . Google Scholar Crossref Search ADS PubMed 29 Chen Y , Zhao W , Lin L , et al. . Nasopharyngeal Epstein-Barr virus load: an efficient supplementary method for population-based nasopharyngeal carcinoma screening . PLoS One . 2015 ; 10 ( 7 ): e0132669 . Google Scholar Crossref Search ADS PubMed 30 Liu SF , Wang H , Li ZJ , et al. . Aspirin induces lytic cytotoxicity in Epstein-Barr virus-positive cells . Eur J Pharmacol . 2008 ; 589 ( 1–3 ): 8 – 13 . Google Scholar Crossref Search ADS PubMed 31 Ordonez P , Nandakumar A , Koriyama C , et al. . Cytotoxic effects of NF-κB inhibitors in combination with anti-herpes agents on Epstein-Barr virus–positive gastric carcinoma in vitro . Mol Med Rep . 2016 ; 14 ( 3 ): 2359 – 2367 . Google Scholar Crossref Search ADS PubMed 32 Chang ET , Cronin-Fenton DP , Friis S , et al. . Aspirin and other nonsteroidal anti-inflammatory drugs in relation to Hodgkin lymphoma risk in northern Denmark . Cancer Epidemiol Biomarkers Prev . 2010 ; 19 ( 1 ): 59 – 64 . Google Scholar Crossref Search ADS PubMed 33 Chang ET , Frøslev T , Sørensen HT , et al. . A nationwide study of aspirin, other non-steroidal anti-inflammatory drugs, and Hodgkin lymphoma risk in Denmark . Br J Cancer . 2011 ; 105 ( 11 ): 1776 – 1782 . Google Scholar Crossref Search ADS PubMed 34 Li J , Shi L , Liang H , et al. . Urban-rural disparities in health care utilization among Chinese adults from 1993 to 2011 . BMC Health Serv Res . 2018 ; 18 : 102 . Google Scholar Crossref Search ADS PubMed Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Journal

American Journal of EpidemiologyOxford University Press

Published: Oct 1, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off