The association between smoking cessation before and after diagnosis and non-muscle-invasive bladder cancer recurrence: a prospective cohort study

The association between smoking cessation before and after diagnosis and non-muscle-invasive... Background Smoking is a major risk factor for bladder cancer, but the relationship between smoking cessation after initial treatment and bladder cancer recurrence has been investigated less frequently and not prospectively yet. Methods 722 non-muscle-invasive bladder cancer (NMIBC) patients (pTa, pT1, and CIS) from the prospective Bladder Cancer Prognosis Programme (BCPP) cohort, selected in the UK between 2005 and 2011, provided complete data on smok- ing behavior before and up to 5 years after diagnosis. The impact of smoking behavior on NMIBC recurrence was explored by multivariable Cox regression models investigating time-to-first NMIBC recurrence. Results Over a median follow-up period of 4.21 years, 403 pathologically confirmed NMIBC recurrences occurred in 210 patients. Only 25 current smokers at diagnosis quit smoking (14%) during follow-up and smoking cessation after diagnosis did not decrease risk of recurrence compared to continuing smokers (p = 0.352). Conclusions Although quitting smoking after diagnosis might reduce the risk of recurrence based on retrospective evidence, this is not confirmed in this prospective study because the number of NMIBC patients quitting smoking before their first recurrence was too low. Nevertheless, this indicates an important role for urologists and other health care professionals in promoting smoking cessation in NMIBC. Keywords Smoking · Smoking cessation · Bladder cancer · Prognosis · Recurrence · Epidemiology Introduction majority of BCs diagnosed are non-muscle-invasive blad- der cancers (NMIBC) [2]. However, NMIBC often recurs Bladder cancer (BC) is estimated to be the ninth most fre- [3] and has a risk of progressing to muscle-invasive bladder quent cancer worldwide with approximately 400,000 newly cancer (MIBC) [4], events which impact on the quality of diagnosed cases per year [1]. Compared to other cancers, life of the patient [5] and generate high disease management mortality rates are generally lower for BC [1] since the costs [6]. * Frits H. M. van Osch University Hospital Birmingham, NHS Foundation Trust, f.vanosch@maastrichtuniversity.nl Birmingham, UK Department of Pharmacology and Toxicology, School Unit of Nutritional and Cancer Epidemiology, Chairgroup for Nutrition and Translational Research in Metabolism of Complex Genetics and Epidemiology, School (NUTRIM), Maastricht University, Maastricht, for Nutrition and Translational Research in Metabolism The Netherlands (NUTRIM), Maastricht University, Maastricht, The Netherlands Chairgroup of Complex Genetics and Epidemiology, Care and Public Health Research Institute (CAPRHI), Maastricht Institute of Cancer and Genomic Sciences, University University, Maastricht, The Netherlands of Birmingham, Birmingham, UK Department of Public Health and Epidemiology, University of Birmingham, Birmingham, UK Vol.:(0123456789) 1 3 676 Cancer Causes & Control (2018) 29:675–683 Although smoking is an established risk factor for BC, its per day), smoking cessation (in years), and tobacco type effects has been less frequently investigated in relation to BC (filter, non-filter, or rolled cigarettes, cigar, or pipe). Monthly prognosis [7–10]. Although many studies investigated effec- smoking status was also assessed retrospectively by postal tiveness of treatment for NMIBC and MIBC with regard to questionnaires that were sent out to participants yearly until recurrence, progression, and mortality, most studies did not the end of follow-up. investigate the effect of smoking or other factors modifi- able by patients on BC prognosis [11]. Nevertheless, the Smoking status at diagnosis and during follow‑up number of studies also reporting hazard ratios (HRs) for BC recurrence by smoking status at diagnosis has increased A combined smoking status variable was created indicat- recently and the current body of evidence consistently shows ing continuing smokers, former smokers who consistently that there is a small association between smoking and BC abstained, never smokers, former smokers who started recurrence when comparing current smokers to never smok- smoking again, and current smokers who quit smoking ers at diagnosis [10, 12]. However, the impact of smoking post-diagnosis. Patients were considered quitters when they cessation after BC diagnosis on recurrence and mortality abstained consistently, so smokers who quit for 3 months has not yet been quantified prospectively [13]. Studies have and then started again were considered as continuing smok- investigated the impact of smoking cessation within 1 year ers. Furthermore, for each participant that reported smoking after diagnosis on BC recurrence, showing a slight decrease cessation during follow-up, it was confirmed whether this in risk of recurrence [14, 15], and one study indicates no occurred before or after their first recurrence. If patients quit effect of quitting after diagnosis on overall or bladder can- smoking after their first recurrence, they were considered as cer-specific mortality [16]. continuing smokers in the time-to-first recurrence analysis. The Bladder Cancer Prognosis Programme (BCPP) fol- lowed up BC patients for 5 years post-diagnosis and investi- Population at risk gated changes in smoking behavior in relation to the course of the disease [17]. The principal aim of this study was to Of the 1,550 cases who agreed to participate, 231 were investigate whether smoking cessation post-diagnosis and subsequently identified as not having BC. Patients who smoking behavior pre-diagnosis influences BC recurrence. presented with MIBC (n = 275) disease at diagnosis were excluded from analysis because they are fundamentally dif- ferent from NMIBC with regard to recurrence. Patients with Methods squamous or adenocarcinomas of non-urothelial origin or with bladder cancer as secondary carcinoma were excluded The Bladder Cancer Prognosis programme (n = 41). In addition to patients presenting with Ta and T1 tumors, carcinoma in situ (CIS) tumors were included This study was conducted within the framework of the West (n = 16) since they have an increased risk of recurrence [18]. Midlands Bladder Cancer Prognosis Programme (BCPP), a In total, 846 (84%) of these patients had provided data on cohort study in the United Kingdom. Details of the study are smoking behavior at diagnosis and during follow-up and described elsewhere [17]. In brief, individuals were included remained under follow-up within the cohort study. Of the between December 2005 and October 2011 after referral to included 846 NMIBC patients, there were 116 patients with participating urology centers due to symptoms suspicious unknown recurrent tumor stage. These 116 unconfirmed of BC and followed for a maximum of 5 years from diag- events were excluded for other analyses as well as 8 cases nosis. Patients with previous cancer of the urethra, bladder, who had radiotherapy (on suspicion of being MIBC cases) ureter, or renal pelvis within the last decade were excluded. resulting in a NMIBC patient population at risk of recur- The study was ethically approved (06/MRE04/65) and all rence of 722. participants gave written informed consent. No systematic guidance or tools were provided to enable patients to quit smoking after diagnosis, so care as usual was Data collection applied by all participating urologists. At or around time of diagnosis, trained research nurses used Statistical analysis semi-structured face-to-face interviews and questionnaires to collect data on social support, health-related quality of BC recurrence was defined as a new tumor that was at the life, sociodemographics, medical history, and health-related same stage as the primary tumor (Ta or T1) but also when behaviors including smoking behavior. Variables on smok- a primary Ta patient had a T1 recurrence. Patients that pro- ing behavior included current smoking status (never, former, gressed from T1 to T2 disease were not counted as a recur- current), duration (years of smoking), intensity (cigarettes rence but as a progression event. Unfortunately, there were 1 3 Cancer Causes & Control (2018) 29:675–683 677 not enough events to also consider biological progression 3 years. Over this period of follow-up, 210 NMIBC patients within this sample of NMIBC patients, as defined in the experienced at least one confirmed recurrence event. These BCPP cohort [19]. Therefore, this study only focussed on 210 NMIBC patients accumulated a total of 403 confirmed confirmed recurrence events and patients who experienced recurrence events in the cohort. a progression event were censored in the survival analysis Most cases were male (79%) and around the age of 70 when the progression event was diagnosed. (Table 1). Furthermore, continuing smokers seemed to be The impact of smoking behavior on BC recurrence was underrepresented in the low EAU risk group (12%), those explored by Cox regression models—with time since initial who quit smoking seemed more likely to be younger and transurethral resection of the bladder tumor (TURBT) as female, and continuing smokers seemed more likely to the time-metric—investigating possible differences in like- present with multiple tumors at diagnosis (Table  1). In lihood of a first recurrence. We explored two different Cox the multivariate models, 26 patients were not included in regression models: one adjusted for age at diagnosis and sex the analysis due to missing data on age (n = 7), number of (model 1) and one additionally adjusted for BC stage, grade, tumors at diagnosis (n = 15), and tumor size (n = 4). Because tumor size, and number of tumors at diagnosis (model 2). participants were recruited from multiple centers, patients This set of confounders was chosen since they are mark- were treated by multiple urologists with different individual ers of NMIBC prognosis and are factors that contribute to thresholds to perform certain therapies. Therefore, not all European Association of Urology (EAU) risk stratification patients were treated exactly according to the EAU guide- for clinical decisions [20]. Moreover, they are potentially lines [20], which is often the case in actual clinical practice associated with smoking behavior at diagnosis [21]. Conse- [25]. quently, conditional risk set modeling was applied to inves- tigate time between multiple recurrent events and analysis time was reset at each event [22]. For this analysis, re-resec- Associations between smoking behavior pre‑ tion of tumors was added to model 2 as a confounder. The and post‑diagnosis and BC recurrence proportional hazards assumption was checked in all models using Schoenfeld residuals. Cumulative incidence functions Although HR estimates for smoking cessation pre-diag- (CIF) corrected for competing risks (death) were made [23]. nosis indicated a protective association with BC recur- Furthermore, the differences in mean number of recur - rence, the p for linear trend was not statistically significant rences over 5 years between never smokers, former smokers, (p = 0.126) and therefore the association cannot be con- trend and continuing smokers were compared using a multivari- sidered as strong (Table 2). No association between smok- able ANOVA model correcting for pairwise comparisons ing status and risk of recurrence was observed in the mul- using Tukey’s HSD. There were not enough BC-related tivariable model (Table 2). Interestingly, when compared death events (45) or confirmed progression events (19) to continuing smokers (HR 1.04, 95% CI 0.65–1.66), HRs to allow for separate analyses. A similarly low number of were similar for those who quit smoking (p = 0.352) and progression events has been observed in a large (n = 718) former smokers who started again post-diagnosis (p = 0.431) NMIBC patient sample before [24]. (Table 2). Additionally, the cumulative incidence function NMIBC patients who died before the end of follow-up shows that cumulative incidence of BC recurrence was low- (n = 157) were censored at time of death, and patients who est for former smokers and never smokers (Fig. 1). underwent cystectomy (n = 15) were censored at the date Only 25 smokers (14%) of the 174 current smokers origi- of cystectomy (13). Other patients were considered lost to nally recorded at diagnosis quit smoking at any point during follow-up when the date on which patients were last seen in follow-up. Three quitters were excluded for full analysis for the hospital for bladder cancer-related therapy or the date on not having information on their date last seen and another which they filled in their last follow-up questionnaire was five had missing data regarding the invasiveness of their before the end of follow-up (5 years). recurrent events. Of the 480 former smokers at diagnosis, 172 (36%) started smoking (any form of tobacco) again post- diagnosis in all included 846 NMIBC patients. Results Exposure to environmental tobacco smoke during child- hood (HR 1.17, 95% CI 0.81–1.68) or adulthood (HR 1.02, Number of recurrences and characteristics 95% CI 0.76–1.36) did not seem to have any impact on time- of population at risk to-first recurrence (Table  2). Table 3 shows HRs for time-to-first recurrence by smok - All 722 patients at risk of recurrence were followed over ing intensity, duration, and pack-years. No linear trends were a median period of 4.21 years (IQR 2.64–5.00 years). The observed although the highest categories showed the highest majority of patients (506, 70%) were followed for at least point estimates for both smoking intensity and pack-years. 1 3 678 Cancer Causes & Control (2018) 29:675–683 Table 1 Patient characteristics at diagnosis and number of recurrences over 5 years for 722 NMIBC patients treated with transurethral resection by smoking category Overall (n = 722) Combined smoking status Never Former Continu- Former smoker who Quitters after p value* smoker smoker ing smoker started again (n = 150) diagnosis (n = 103) (n = 266) (n = 186) (n = 17) Age in years < 0.001  Median (25th– 71 (63–77) 72 (61–79) 72 (67–79) 67 (57–74) 72 (64–77) 62 (56–67) 75th percentile) Sex < 0.001  Male 573 (79%) 63 (61%) 231 (87%) 139 (75%) 129 (86%) 11 (65%)  Female 149 (21%) 40 (39%) 35 (13%) 47 (25%) 21 (14%) 6 (35%) EAU risk group < 0.001  Low 128 (18%) 28 (27%) 71 (27%) 23 (12%) 4 (3%) 2 (12%)  Intermediate 383(53%) 50 (49%) 131 (49%) 97 (52%) 91 (61%) 14 (82%)  High 211 (29%) 25 (24%) 64 (24%) 66 (36%) 55 (37%) 1 (6%) Number of tumors < 0.001  1 429 (61%) 70 (70%) 179 (69%) 100 (55%) 69 (46%) 11 (65%)  2–7 258 (36%) 27 (27%) 74 (28%) 76 (42%) 75 (50%) 6 (35%)  ≥ 8 22 (3%) 3 (3%) 8 (3%) 6 (3%) 5 (3%) 0 (-) Tumor size 0.068  < 3 cm 445 (63%) 68 (68%) 174 (67%) 105 (58%) 85 (57%) 13 (76%)  ≥ 3 cm 260 (37%) 32 (32%) 84 (33%) 77 (42%) 63 (43%) 4 (24%) Grade 0.001  1 212 (30%) 34 (34%) 99 (38%) 51 (28%) 26 (17%) 2 (13%)  2 257 (36%) 34 (34%) 75 (28%) 73 (40%) 66 (44%) 9 (56%)  3 245 (34%) 33 (33%) 90 (34%) 60 (32%) 57 (38%) 5 (31%) Stage 0.590  pTa 476 (66%) 68 (66%) 184 (69%) 115 (62%) 95 (63%) 14 (82%)  pT1 239 (33%) 35 (34%) 79 (30%) 69 (37%) 53 (35%) 3 (18%)  pCis 7 (1%) 0 (-) 3 (1%) 2 (1%) 2 (1%) 0 (-) No of recurrences 0.337  1 108 (51%) 18 (62%) 28 (46%) 33 (53%) 27 (52%) 2 (33%)  2 46 (22%) 6 (21%) 16 (26%) 16 (26%) 6 (11%) 2 (33%)  > 3 56 (27%) 5 (17%) 17 (28%) 13 (21%) 19 (37%) 2 (33%) Smoking intensity 0.076  1–9 cigarettes 128 (29%) NA 55 (30%) 23 (21%) 42 (34%) 8 (50%)  10–19 cigarettes 140 (32%) NA 53 (28%) 42 (38%) 42 (34%) 3 (19%)  >20 cigarettes 167 (38%) NA 78 (42%) 45 (41%) 39 (32%) 5 (31%) Smoking duration < 0.001  1–9 years 45 (10%) NA 26 (14%) 2 (2%) 16(14%) 1 (6%)  10–19 years 83 (19%) NA 43 (23%) 10 (9%) 29 (25%) 1 (6%)  20–29 years 87 (20%) NA 46 (25%) 12 (11%) 27 (23%) 2 (13%)  30–39 years 88 (21%) NA 37 (20%) 28 (25%) 19 (16%) 4 (25%)  > 40 years 127 (30%) NA 32 (17%) 60 (54%) 27 (23%) 8 (50%) Smoking cessation 0.051  < 20 years 48 (12%) NA 23 (9%) NA 25 (17%) NA  21–40 years 208 (51%) NA 134 (51%) NA 74 (49%) NA  > 40 years 155 (38%) NA 104 (40%) NA 51 (34%) NA *Kruskal–Wallis test for continuous and Chi-square test for categorical variables 1 3 Cancer Causes & Control (2018) 29:675–683 679 Table 2 Cox regression analysis investigating the association between combined smoking status, smoking cessation before diagnosis and passive smoking, and time-to-first recurrence in NMIBC patients treated with TURBT Age and sex adjusted Multivariable model* HR 95% CI Number of events/ HR 95% CI Number of patients at risk events/patients at risk Combined smoking status  Never smoker 1.00 Ref. 29/103 1.00 Ref. 28/99  Former smoker 0.79 0.51–1.24 61/266 0.78 0.48–1.24 59/254  Continuing smoker 1.17 0.75–1.83 62/186 1.04 0.65–1.66 61/180  Former smoker who started again** 1.04 0.65–1.64 51/150 0.87 0.53–1.41 49/146  Current smoker who quit smoking*** 1.25 0.52-3.00 6/17 1.47 0.63–3.41 6/17 Smoking cessation (in years)****  < 20 years 0.81 0.46–1.43 15/48 0.82 0.46–1.46 15/47  21–40 years 0.76 0.53–1.08 57/208 0.74 0.51–1.08 54/200  > 40 years 0.67 0.44–1.02 39/155 0.71 0.46–1.09 38/148 p for trend 0.070 0.126 Exposed to passive smoking during childhood?  No 1.00 Ref. 36/142 1.00 Ref. 35/138  Yes 1.23 0.86–1.75 173/576 1.17 0.81–1.68 168/554 Exposed to passive smoking during adulthood?  No 1.00 Ref. 74/261 1.00 Ref. 74/261  Yes 1.03 0.77–1.38 135/454 1.02 0.76–1.36 135/454 *All estimates adjusted for age, sex, stage, grade, tumor size, and number of tumors **Former smoker who started again and current smoker who quit smoking not included in former smokers at diagnosis ***Smokers who quit after their first event are considered as current smokers ****Reference category = current smokers at diagnosis, estimates also include former smokers who started again after diagnosis recurrence analysis (HR for continuing vs. never smokers is 1.10, 95% CI = 0.72–1.69). However, continuing smokers seemed to have experienced more recurrences than never smokers on average over 5 years on average, however not significantly (0.64 vs. 0.45, p = 0.308). Discussion Smoking cessation post‑diagnosis and BC recurrence and clinical implications The reported HRs give reason to believe that quitting smok- ing does not influence the likelihood of NMIBC recurrence over 5 years when compared to continuing smokers in our Fig. 1 Cumulative incidence functions with correction for competing sample. However, the number of quitters in our prospec- risk (death) indicating cumulative incidence of first recurrence per category of smoking status in NMIBC patients treated with TURBT tive sample was small which complicates drawing conclu- sions for this group. Another (retrospective) patient cohort study which assessed smoking cessation post-diagnosis concluded that quitting smoking significantly reduced risk For smoking duration, the HRs were divergent and did not indicate any trend (p = 0.729) at all. of recurrence (HR 0.45, 95% CI 0.25–0.83, comparing trend quitters to continuing smokers); however, the proportion of When considering multiple events that have occurred in patients (Table 4), the HRs are similar to the time-to-first quitters (~ 43% of current smokers at diagnosis) was also 1 3 680 Cancer Causes & Control (2018) 29:675–683 Table 3 Multivariable Cox Age and sex adjusted Multivariable model* regression analysis concerning the association between HR 95% CI Number of events/ HR 95% CI Number of smoking pack-years, intensity, patients at risk events/patients and duration (recorded at at risk diagnosis) with time-to-first Never smoker 1.00 Ref. 29/103 1.00 Ref. 28/99 recurrence in NMIBC patients treated with TURBT Pack-years  1–9 pack-years 0.86 0.53–1.42 36/141 0.81 0.48–1.37 34/134  10–19 pack-years 0.95 0.54–1.67 22/81 0.92 0.51–1.65 22/80  20–29 pack-years 0.93 0.49–1.77 15/58 0.81 0.42–1.60 15/57  30–39 pack-years 0.70 0.35–1.43 11/55 0.60 0.30–1.22 11/53  > 40 pack-years 1.28 0.76–2.14 30/86 1.14 0.66–1.97 29/83 p for trend 0.365 0.688 Smoking intensity (cigarettes/day)  1–9 cigarettes 0.83 0.50–1.38 32/128 0.81 0.47–1.38 30/122  10–19 cigarettes 0.75 0.45–1.28 31/140 0.61 0.35–1.07 31/138  20+ cigarettes 1.24 0.79–1.96 55/167 1.16 0.72–1.85 54/160 p for trend 0.112 0.198 Smoking duration (in years)  1–9 years 1.03 0.52–2.05 12/45 0.97 0.48–1.95 12/43  10–19 years 0.94 0.54–1.62 22/83 0.85 0.48–1.50 21/78  20–29 years 0.79 0.45–1.39 21/87 0.79 0.44–1.44 20/85  30–39 years 1.08 0.61–1.89 26/88 0.93 0.52–1.66 25/85  40+ years 1.00 0.60–1.64 36/127 0.88 0.52–1.49 36/124 p for trend 0.917 0.729 *All estimates adjusted for age, sex, stage, grade, tumor size, and number of tumors at diagnosis Table 4 Conditional risk HR* 95% CI Number of Mean number of recur- set model investigating time events/patients rences over 5 years (95% between multiple recurrence at risk CI) events in NMIBC patients treated with TURBT by Smoking status smoking status at diagnosis and  Never smoker 1.00 Ref. 43/99 0.45 (0.28–0.63) after diagnosis  Former smoker 0.71 0.47–1.08 108/254 0.45 (0.33–0.57)  Continuing smoker 1.10 0.72–1.69 116/180 0.64 (0.47–0.81)  Former smoker who started again 0.89 0.56–1.43 108/146 0.82 (0.57–1.06)  Current smoker who quit smoking** 0.85 0.35–2.04 18/19 0.84 (0.10–1.58) *All estimates adjusted for age, sex, stage, grade, tumor size, number of tumors, and re-resection of recur- rent tumor **Smokers who have quit after their first event (n = 2) are also included considerably larger [14]. In another retrospective cohort as lung cancer where this association is stronger, evidence to study, Fleshner et al. concluded that it remained unclear imply a strong, causal relationship between smoking behav- whether smoking cessation at time of diagnosis is benefi- ior after diagnosis and recurrence is still limited [27]; so cial with regard to BC recurrence [15] although Aveyard more prospective research is needed. et al. estimated that the Fleshner study shows a HR of 0.71 Considering the prolonged latency period for the develop- (95% CI 0.48–1.05) when comparing quitters to continuing ment of BC after exposures [2], it is credible that the asso- smokers [26], which is similar to the estimate observed in ciation between altering smoking behavior post-diagnosis the study by Chen et al. Taken together, the limited evidence and likelihood of a first recurrence or multiple recurrences at this point seems to indicate that quitting smoking at or over 5  years is not as strong as the association between closely after diagnosis could reduce risk of recurrence. How- smoking and carcinogenesis. Similarly, epidemiological ever, even across several smoking-related cancer sites such evidence suggests that pre-diagnostic smoking cessation 1 3 Cancer Causes & Control (2018) 29:675–683 681 does not immediately lower the risk of BC [28], also indi- tumors. This theory of “field cancerization” proposes that cating a longer latency period than 5 years. Furthermore, it (pre-)malignant transformation of cells has already occurred is considered that a first BC recurrence is often the result of at different sites across the urothelium, explaining why incomplete resection and/or tumor cell re-implantation, and (changing) smoking exposure will not have a large impact that genuine new tumor formation only plays a more impor- on disease prognosis [36]. tant role in later recurrences [29]. It is therefore reasonable Additionally, given that recent reviews indicate no con- to suggest that, because of the DNA-damaging effects of siderable heterogeneity between studies that do not show an cigarette smoke [30], modifying smoking behavior may only association between environmental tobacco smoke and risk influence later recurrences and possibly those that may occur of BC, it is unlikely that we would have shown any substan- beyond the follow-up period of 5 years reported here. tial association with BC recurrence either [37, 38]. Notwithstanding the results from our study, when consid- Because no substantial association between smoking ering the impact of comorbidities on overall survival in BC status pre-diagnosis and BC recurrence was observed in patients [31] which include several smoking-related diseases adjusted models it is possible that the tumor characteristics [32] and other evidence indicating beneficial and significant associated with BC recurrence (stage, grade, tumor size, results of post-diagnostic smoking cessation in retrospective number of tumors) included as confounders in these models studies [14, 15], it is evident that smoking cessation should overshadow the effects of smoking behavior in determining be encouraged for NMIBC patients at diagnosis. risk of BC recurrence [21] and possible also mortality since It is striking that only 14% of current smokers at diag- no association between quitting smoking after diagnosis and nosis in our sample quit smoking post-diagnosis. There are all-cause or bladder cancer-specific mortality was observed examples of successful smoking cessation interventions in in a large retrospective cohort study [16]. Moreover, since urology [33], and several studies found that when patients current smokers at diagnosis in our cohort have been asso- were diagnosed with BC they were more likely to quit ciated with having a higher stage, higher grade, and larger smoking [34, 35]. Therefore, urologists should continue to tumor size compared to never smokers [39], smoking behav- improve smoking cessation counseling in newly diagnosed ior might play a more crucial role in determining risk of NMIBC patients and be updated on the available tools to recurrence already before diagnosis through promoting unfa- improve smoking cessation figures. Moreover, more inter - vorable tumor characteristics associated with BC recurrence vention clinical research investigating smoking cessation at diagnosis, although in a Dutch cohort of 323 UBC patients programmes in NMIBC patients is warranted. there was only a weak association between smoking inten- sity and increased risk of a more aggressive tumor type [40]. Smoking behavior pre‑diagnosis and exposure to environmental tobacco smoke Strengths and weaknesses Smoking cessation was most beneficial, with regard to Despite the prospective nature of our study there were some reducing the risk of recurrence, the longer before diagnosis limitations restricting the analyses. Due to the relatively it happened compared to continuing smokers. This was the short follow-up of this study, long-term effects of smoking strongest association observed in our study and has been cessation post-diagnosis could not be assessed and the num- observed in other studies as well, although not consistently ber of deaths due to BC in the NMIBC patients within our [12]. Other results were in line with earlier studies inves- cohort was too low for Cox regression analysis. Also, it was tigating smoking status at diagnosis and BC recurrence as not possible to obtain detailed information on adjuvant ther- well, by indicating a slightly increased risk of recurrence apy for all patients, so differences in adjuvant therapy could in NMIBC patients for current smokers compared to never not be considered in the statistical analysis. Additionally, smokers in a meta-analysis [10]. we did not correct for biomarkers of BC recurrence such as Another recent study not included in the aforemen- mutations in the FGFR3 or TP53 genes [41], although they tioned meta-analysis shows similar HRs (HR 1.49, 95% might work together with smoking intensity in predicting CI 0.95–2.33) for current smokers at diagnosis [8]. How- BC outcome [42]. ever, when including this study and our study (data from Furthermore, one of the caveats of using only self- continuing smokers) in the meta-analysis, the pooled HR reported questionnaire data to assess smoking exposure barely changes from 1.27 (95% CI 1.09–1.46) to 1.26 (95% was likely demonstrated in our sample of NMIBC patients. CI 1.12–1.40) [10], indicating a significantly increased risk The large proportion (about 1 in 3) of former smokers pre- of recurrence for current smokers at diagnosis compared to diagnosis who reported to have started smoking again post- never smokers. Possibly, the lack of association for continu- diagnosis is implausible and is probably observed due to ing smokers in this study can be explained through multiple misclassification of either the questionnaire at baseline or synchronous tumors being present at diagnosis in epithelial during follow-up. A high misclassification rate (47%) when 1 3 682 Cancer Causes & Control (2018) 29:675–683 5. Roychowdhury DF, Hayden A, Liepa AM (2003) Health-related comparing self-reported data on smoking behavior to coti- quality-of-life parameters as independent prognostic factors in nine values in blood was also shown in another sample of advanced or metastatic bladder cancer. J Clin Oncol 21:673–678 bladder cancer patients undergoing surveillance [43]. Prefer- 6. Svatek RS, Hollenbeck BK, Holmäng S, Lee R, Kim SP, Stenzl ably, future studies should consider more reliable ways of A et al (2014) The economics of bladder cancer: costs and con- siderations of caring for this disease. Eur Urol 66:253–262. https verifying smoking exposure through biochemical analysis. ://doi.org/10.1016/j.eurur o.2014.01.006 Unfortunately, at the start of the study we did not antici- 7. Hou L, Hong X, Dai M, Chen P, Zhao H, Wei Q et al (2016) pate this small proportion of quitters after diagnosis which Association of smoking status with prognosis in bladder cancer: is why the analysis concerning quitters is underpowered. a meta-analysis. Oncotarget Impact J. https ://doi.org/10.18632 / oncot arget .13606 8. Li HM, Azhati B, Rexiati M, Wang WG, Li XD, Liu Q et al (2016) Impact of smoking status and cumulative smoking exposure on tumor recurrence of non-muscle-invasive bladder cancer. Int Urol Conclusion Nephrol. https ://doi.org/10.1007/s1125 5-016-1441-6 9. 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The association between smoking cessation before and after diagnosis and non-muscle-invasive bladder cancer recurrence: a prospective cohort study

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Biomedicine; Cancer Research; Biomedicine, general; Oncology; Public Health; Epidemiology; Hematology
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Abstract

Background Smoking is a major risk factor for bladder cancer, but the relationship between smoking cessation after initial treatment and bladder cancer recurrence has been investigated less frequently and not prospectively yet. Methods 722 non-muscle-invasive bladder cancer (NMIBC) patients (pTa, pT1, and CIS) from the prospective Bladder Cancer Prognosis Programme (BCPP) cohort, selected in the UK between 2005 and 2011, provided complete data on smok- ing behavior before and up to 5 years after diagnosis. The impact of smoking behavior on NMIBC recurrence was explored by multivariable Cox regression models investigating time-to-first NMIBC recurrence. Results Over a median follow-up period of 4.21 years, 403 pathologically confirmed NMIBC recurrences occurred in 210 patients. Only 25 current smokers at diagnosis quit smoking (14%) during follow-up and smoking cessation after diagnosis did not decrease risk of recurrence compared to continuing smokers (p = 0.352). Conclusions Although quitting smoking after diagnosis might reduce the risk of recurrence based on retrospective evidence, this is not confirmed in this prospective study because the number of NMIBC patients quitting smoking before their first recurrence was too low. Nevertheless, this indicates an important role for urologists and other health care professionals in promoting smoking cessation in NMIBC. Keywords Smoking · Smoking cessation · Bladder cancer · Prognosis · Recurrence · Epidemiology Introduction majority of BCs diagnosed are non-muscle-invasive blad- der cancers (NMIBC) [2]. However, NMIBC often recurs Bladder cancer (BC) is estimated to be the ninth most fre- [3] and has a risk of progressing to muscle-invasive bladder quent cancer worldwide with approximately 400,000 newly cancer (MIBC) [4], events which impact on the quality of diagnosed cases per year [1]. Compared to other cancers, life of the patient [5] and generate high disease management mortality rates are generally lower for BC [1] since the costs [6]. * Frits H. M. van Osch University Hospital Birmingham, NHS Foundation Trust, f.vanosch@maastrichtuniversity.nl Birmingham, UK Department of Pharmacology and Toxicology, School Unit of Nutritional and Cancer Epidemiology, Chairgroup for Nutrition and Translational Research in Metabolism of Complex Genetics and Epidemiology, School (NUTRIM), Maastricht University, Maastricht, for Nutrition and Translational Research in Metabolism The Netherlands (NUTRIM), Maastricht University, Maastricht, The Netherlands Chairgroup of Complex Genetics and Epidemiology, Care and Public Health Research Institute (CAPRHI), Maastricht Institute of Cancer and Genomic Sciences, University University, Maastricht, The Netherlands of Birmingham, Birmingham, UK Department of Public Health and Epidemiology, University of Birmingham, Birmingham, UK Vol.:(0123456789) 1 3 676 Cancer Causes & Control (2018) 29:675–683 Although smoking is an established risk factor for BC, its per day), smoking cessation (in years), and tobacco type effects has been less frequently investigated in relation to BC (filter, non-filter, or rolled cigarettes, cigar, or pipe). Monthly prognosis [7–10]. Although many studies investigated effec- smoking status was also assessed retrospectively by postal tiveness of treatment for NMIBC and MIBC with regard to questionnaires that were sent out to participants yearly until recurrence, progression, and mortality, most studies did not the end of follow-up. investigate the effect of smoking or other factors modifi- able by patients on BC prognosis [11]. Nevertheless, the Smoking status at diagnosis and during follow‑up number of studies also reporting hazard ratios (HRs) for BC recurrence by smoking status at diagnosis has increased A combined smoking status variable was created indicat- recently and the current body of evidence consistently shows ing continuing smokers, former smokers who consistently that there is a small association between smoking and BC abstained, never smokers, former smokers who started recurrence when comparing current smokers to never smok- smoking again, and current smokers who quit smoking ers at diagnosis [10, 12]. However, the impact of smoking post-diagnosis. Patients were considered quitters when they cessation after BC diagnosis on recurrence and mortality abstained consistently, so smokers who quit for 3 months has not yet been quantified prospectively [13]. Studies have and then started again were considered as continuing smok- investigated the impact of smoking cessation within 1 year ers. Furthermore, for each participant that reported smoking after diagnosis on BC recurrence, showing a slight decrease cessation during follow-up, it was confirmed whether this in risk of recurrence [14, 15], and one study indicates no occurred before or after their first recurrence. If patients quit effect of quitting after diagnosis on overall or bladder can- smoking after their first recurrence, they were considered as cer-specific mortality [16]. continuing smokers in the time-to-first recurrence analysis. The Bladder Cancer Prognosis Programme (BCPP) fol- lowed up BC patients for 5 years post-diagnosis and investi- Population at risk gated changes in smoking behavior in relation to the course of the disease [17]. The principal aim of this study was to Of the 1,550 cases who agreed to participate, 231 were investigate whether smoking cessation post-diagnosis and subsequently identified as not having BC. Patients who smoking behavior pre-diagnosis influences BC recurrence. presented with MIBC (n = 275) disease at diagnosis were excluded from analysis because they are fundamentally dif- ferent from NMIBC with regard to recurrence. Patients with Methods squamous or adenocarcinomas of non-urothelial origin or with bladder cancer as secondary carcinoma were excluded The Bladder Cancer Prognosis programme (n = 41). In addition to patients presenting with Ta and T1 tumors, carcinoma in situ (CIS) tumors were included This study was conducted within the framework of the West (n = 16) since they have an increased risk of recurrence [18]. Midlands Bladder Cancer Prognosis Programme (BCPP), a In total, 846 (84%) of these patients had provided data on cohort study in the United Kingdom. Details of the study are smoking behavior at diagnosis and during follow-up and described elsewhere [17]. In brief, individuals were included remained under follow-up within the cohort study. Of the between December 2005 and October 2011 after referral to included 846 NMIBC patients, there were 116 patients with participating urology centers due to symptoms suspicious unknown recurrent tumor stage. These 116 unconfirmed of BC and followed for a maximum of 5 years from diag- events were excluded for other analyses as well as 8 cases nosis. Patients with previous cancer of the urethra, bladder, who had radiotherapy (on suspicion of being MIBC cases) ureter, or renal pelvis within the last decade were excluded. resulting in a NMIBC patient population at risk of recur- The study was ethically approved (06/MRE04/65) and all rence of 722. participants gave written informed consent. No systematic guidance or tools were provided to enable patients to quit smoking after diagnosis, so care as usual was Data collection applied by all participating urologists. At or around time of diagnosis, trained research nurses used Statistical analysis semi-structured face-to-face interviews and questionnaires to collect data on social support, health-related quality of BC recurrence was defined as a new tumor that was at the life, sociodemographics, medical history, and health-related same stage as the primary tumor (Ta or T1) but also when behaviors including smoking behavior. Variables on smok- a primary Ta patient had a T1 recurrence. Patients that pro- ing behavior included current smoking status (never, former, gressed from T1 to T2 disease were not counted as a recur- current), duration (years of smoking), intensity (cigarettes rence but as a progression event. Unfortunately, there were 1 3 Cancer Causes & Control (2018) 29:675–683 677 not enough events to also consider biological progression 3 years. Over this period of follow-up, 210 NMIBC patients within this sample of NMIBC patients, as defined in the experienced at least one confirmed recurrence event. These BCPP cohort [19]. Therefore, this study only focussed on 210 NMIBC patients accumulated a total of 403 confirmed confirmed recurrence events and patients who experienced recurrence events in the cohort. a progression event were censored in the survival analysis Most cases were male (79%) and around the age of 70 when the progression event was diagnosed. (Table 1). Furthermore, continuing smokers seemed to be The impact of smoking behavior on BC recurrence was underrepresented in the low EAU risk group (12%), those explored by Cox regression models—with time since initial who quit smoking seemed more likely to be younger and transurethral resection of the bladder tumor (TURBT) as female, and continuing smokers seemed more likely to the time-metric—investigating possible differences in like- present with multiple tumors at diagnosis (Table  1). In lihood of a first recurrence. We explored two different Cox the multivariate models, 26 patients were not included in regression models: one adjusted for age at diagnosis and sex the analysis due to missing data on age (n = 7), number of (model 1) and one additionally adjusted for BC stage, grade, tumors at diagnosis (n = 15), and tumor size (n = 4). Because tumor size, and number of tumors at diagnosis (model 2). participants were recruited from multiple centers, patients This set of confounders was chosen since they are mark- were treated by multiple urologists with different individual ers of NMIBC prognosis and are factors that contribute to thresholds to perform certain therapies. Therefore, not all European Association of Urology (EAU) risk stratification patients were treated exactly according to the EAU guide- for clinical decisions [20]. Moreover, they are potentially lines [20], which is often the case in actual clinical practice associated with smoking behavior at diagnosis [21]. Conse- [25]. quently, conditional risk set modeling was applied to inves- tigate time between multiple recurrent events and analysis time was reset at each event [22]. For this analysis, re-resec- Associations between smoking behavior pre‑ tion of tumors was added to model 2 as a confounder. The and post‑diagnosis and BC recurrence proportional hazards assumption was checked in all models using Schoenfeld residuals. Cumulative incidence functions Although HR estimates for smoking cessation pre-diag- (CIF) corrected for competing risks (death) were made [23]. nosis indicated a protective association with BC recur- Furthermore, the differences in mean number of recur - rence, the p for linear trend was not statistically significant rences over 5 years between never smokers, former smokers, (p = 0.126) and therefore the association cannot be con- trend and continuing smokers were compared using a multivari- sidered as strong (Table 2). No association between smok- able ANOVA model correcting for pairwise comparisons ing status and risk of recurrence was observed in the mul- using Tukey’s HSD. There were not enough BC-related tivariable model (Table 2). Interestingly, when compared death events (45) or confirmed progression events (19) to continuing smokers (HR 1.04, 95% CI 0.65–1.66), HRs to allow for separate analyses. A similarly low number of were similar for those who quit smoking (p = 0.352) and progression events has been observed in a large (n = 718) former smokers who started again post-diagnosis (p = 0.431) NMIBC patient sample before [24]. (Table 2). Additionally, the cumulative incidence function NMIBC patients who died before the end of follow-up shows that cumulative incidence of BC recurrence was low- (n = 157) were censored at time of death, and patients who est for former smokers and never smokers (Fig. 1). underwent cystectomy (n = 15) were censored at the date Only 25 smokers (14%) of the 174 current smokers origi- of cystectomy (13). Other patients were considered lost to nally recorded at diagnosis quit smoking at any point during follow-up when the date on which patients were last seen in follow-up. Three quitters were excluded for full analysis for the hospital for bladder cancer-related therapy or the date on not having information on their date last seen and another which they filled in their last follow-up questionnaire was five had missing data regarding the invasiveness of their before the end of follow-up (5 years). recurrent events. Of the 480 former smokers at diagnosis, 172 (36%) started smoking (any form of tobacco) again post- diagnosis in all included 846 NMIBC patients. Results Exposure to environmental tobacco smoke during child- hood (HR 1.17, 95% CI 0.81–1.68) or adulthood (HR 1.02, Number of recurrences and characteristics 95% CI 0.76–1.36) did not seem to have any impact on time- of population at risk to-first recurrence (Table  2). Table 3 shows HRs for time-to-first recurrence by smok - All 722 patients at risk of recurrence were followed over ing intensity, duration, and pack-years. No linear trends were a median period of 4.21 years (IQR 2.64–5.00 years). The observed although the highest categories showed the highest majority of patients (506, 70%) were followed for at least point estimates for both smoking intensity and pack-years. 1 3 678 Cancer Causes & Control (2018) 29:675–683 Table 1 Patient characteristics at diagnosis and number of recurrences over 5 years for 722 NMIBC patients treated with transurethral resection by smoking category Overall (n = 722) Combined smoking status Never Former Continu- Former smoker who Quitters after p value* smoker smoker ing smoker started again (n = 150) diagnosis (n = 103) (n = 266) (n = 186) (n = 17) Age in years < 0.001  Median (25th– 71 (63–77) 72 (61–79) 72 (67–79) 67 (57–74) 72 (64–77) 62 (56–67) 75th percentile) Sex < 0.001  Male 573 (79%) 63 (61%) 231 (87%) 139 (75%) 129 (86%) 11 (65%)  Female 149 (21%) 40 (39%) 35 (13%) 47 (25%) 21 (14%) 6 (35%) EAU risk group < 0.001  Low 128 (18%) 28 (27%) 71 (27%) 23 (12%) 4 (3%) 2 (12%)  Intermediate 383(53%) 50 (49%) 131 (49%) 97 (52%) 91 (61%) 14 (82%)  High 211 (29%) 25 (24%) 64 (24%) 66 (36%) 55 (37%) 1 (6%) Number of tumors < 0.001  1 429 (61%) 70 (70%) 179 (69%) 100 (55%) 69 (46%) 11 (65%)  2–7 258 (36%) 27 (27%) 74 (28%) 76 (42%) 75 (50%) 6 (35%)  ≥ 8 22 (3%) 3 (3%) 8 (3%) 6 (3%) 5 (3%) 0 (-) Tumor size 0.068  < 3 cm 445 (63%) 68 (68%) 174 (67%) 105 (58%) 85 (57%) 13 (76%)  ≥ 3 cm 260 (37%) 32 (32%) 84 (33%) 77 (42%) 63 (43%) 4 (24%) Grade 0.001  1 212 (30%) 34 (34%) 99 (38%) 51 (28%) 26 (17%) 2 (13%)  2 257 (36%) 34 (34%) 75 (28%) 73 (40%) 66 (44%) 9 (56%)  3 245 (34%) 33 (33%) 90 (34%) 60 (32%) 57 (38%) 5 (31%) Stage 0.590  pTa 476 (66%) 68 (66%) 184 (69%) 115 (62%) 95 (63%) 14 (82%)  pT1 239 (33%) 35 (34%) 79 (30%) 69 (37%) 53 (35%) 3 (18%)  pCis 7 (1%) 0 (-) 3 (1%) 2 (1%) 2 (1%) 0 (-) No of recurrences 0.337  1 108 (51%) 18 (62%) 28 (46%) 33 (53%) 27 (52%) 2 (33%)  2 46 (22%) 6 (21%) 16 (26%) 16 (26%) 6 (11%) 2 (33%)  > 3 56 (27%) 5 (17%) 17 (28%) 13 (21%) 19 (37%) 2 (33%) Smoking intensity 0.076  1–9 cigarettes 128 (29%) NA 55 (30%) 23 (21%) 42 (34%) 8 (50%)  10–19 cigarettes 140 (32%) NA 53 (28%) 42 (38%) 42 (34%) 3 (19%)  >20 cigarettes 167 (38%) NA 78 (42%) 45 (41%) 39 (32%) 5 (31%) Smoking duration < 0.001  1–9 years 45 (10%) NA 26 (14%) 2 (2%) 16(14%) 1 (6%)  10–19 years 83 (19%) NA 43 (23%) 10 (9%) 29 (25%) 1 (6%)  20–29 years 87 (20%) NA 46 (25%) 12 (11%) 27 (23%) 2 (13%)  30–39 years 88 (21%) NA 37 (20%) 28 (25%) 19 (16%) 4 (25%)  > 40 years 127 (30%) NA 32 (17%) 60 (54%) 27 (23%) 8 (50%) Smoking cessation 0.051  < 20 years 48 (12%) NA 23 (9%) NA 25 (17%) NA  21–40 years 208 (51%) NA 134 (51%) NA 74 (49%) NA  > 40 years 155 (38%) NA 104 (40%) NA 51 (34%) NA *Kruskal–Wallis test for continuous and Chi-square test for categorical variables 1 3 Cancer Causes & Control (2018) 29:675–683 679 Table 2 Cox regression analysis investigating the association between combined smoking status, smoking cessation before diagnosis and passive smoking, and time-to-first recurrence in NMIBC patients treated with TURBT Age and sex adjusted Multivariable model* HR 95% CI Number of events/ HR 95% CI Number of patients at risk events/patients at risk Combined smoking status  Never smoker 1.00 Ref. 29/103 1.00 Ref. 28/99  Former smoker 0.79 0.51–1.24 61/266 0.78 0.48–1.24 59/254  Continuing smoker 1.17 0.75–1.83 62/186 1.04 0.65–1.66 61/180  Former smoker who started again** 1.04 0.65–1.64 51/150 0.87 0.53–1.41 49/146  Current smoker who quit smoking*** 1.25 0.52-3.00 6/17 1.47 0.63–3.41 6/17 Smoking cessation (in years)****  < 20 years 0.81 0.46–1.43 15/48 0.82 0.46–1.46 15/47  21–40 years 0.76 0.53–1.08 57/208 0.74 0.51–1.08 54/200  > 40 years 0.67 0.44–1.02 39/155 0.71 0.46–1.09 38/148 p for trend 0.070 0.126 Exposed to passive smoking during childhood?  No 1.00 Ref. 36/142 1.00 Ref. 35/138  Yes 1.23 0.86–1.75 173/576 1.17 0.81–1.68 168/554 Exposed to passive smoking during adulthood?  No 1.00 Ref. 74/261 1.00 Ref. 74/261  Yes 1.03 0.77–1.38 135/454 1.02 0.76–1.36 135/454 *All estimates adjusted for age, sex, stage, grade, tumor size, and number of tumors **Former smoker who started again and current smoker who quit smoking not included in former smokers at diagnosis ***Smokers who quit after their first event are considered as current smokers ****Reference category = current smokers at diagnosis, estimates also include former smokers who started again after diagnosis recurrence analysis (HR for continuing vs. never smokers is 1.10, 95% CI = 0.72–1.69). However, continuing smokers seemed to have experienced more recurrences than never smokers on average over 5 years on average, however not significantly (0.64 vs. 0.45, p = 0.308). Discussion Smoking cessation post‑diagnosis and BC recurrence and clinical implications The reported HRs give reason to believe that quitting smok- ing does not influence the likelihood of NMIBC recurrence over 5 years when compared to continuing smokers in our Fig. 1 Cumulative incidence functions with correction for competing sample. However, the number of quitters in our prospec- risk (death) indicating cumulative incidence of first recurrence per category of smoking status in NMIBC patients treated with TURBT tive sample was small which complicates drawing conclu- sions for this group. Another (retrospective) patient cohort study which assessed smoking cessation post-diagnosis concluded that quitting smoking significantly reduced risk For smoking duration, the HRs were divergent and did not indicate any trend (p = 0.729) at all. of recurrence (HR 0.45, 95% CI 0.25–0.83, comparing trend quitters to continuing smokers); however, the proportion of When considering multiple events that have occurred in patients (Table 4), the HRs are similar to the time-to-first quitters (~ 43% of current smokers at diagnosis) was also 1 3 680 Cancer Causes & Control (2018) 29:675–683 Table 3 Multivariable Cox Age and sex adjusted Multivariable model* regression analysis concerning the association between HR 95% CI Number of events/ HR 95% CI Number of smoking pack-years, intensity, patients at risk events/patients and duration (recorded at at risk diagnosis) with time-to-first Never smoker 1.00 Ref. 29/103 1.00 Ref. 28/99 recurrence in NMIBC patients treated with TURBT Pack-years  1–9 pack-years 0.86 0.53–1.42 36/141 0.81 0.48–1.37 34/134  10–19 pack-years 0.95 0.54–1.67 22/81 0.92 0.51–1.65 22/80  20–29 pack-years 0.93 0.49–1.77 15/58 0.81 0.42–1.60 15/57  30–39 pack-years 0.70 0.35–1.43 11/55 0.60 0.30–1.22 11/53  > 40 pack-years 1.28 0.76–2.14 30/86 1.14 0.66–1.97 29/83 p for trend 0.365 0.688 Smoking intensity (cigarettes/day)  1–9 cigarettes 0.83 0.50–1.38 32/128 0.81 0.47–1.38 30/122  10–19 cigarettes 0.75 0.45–1.28 31/140 0.61 0.35–1.07 31/138  20+ cigarettes 1.24 0.79–1.96 55/167 1.16 0.72–1.85 54/160 p for trend 0.112 0.198 Smoking duration (in years)  1–9 years 1.03 0.52–2.05 12/45 0.97 0.48–1.95 12/43  10–19 years 0.94 0.54–1.62 22/83 0.85 0.48–1.50 21/78  20–29 years 0.79 0.45–1.39 21/87 0.79 0.44–1.44 20/85  30–39 years 1.08 0.61–1.89 26/88 0.93 0.52–1.66 25/85  40+ years 1.00 0.60–1.64 36/127 0.88 0.52–1.49 36/124 p for trend 0.917 0.729 *All estimates adjusted for age, sex, stage, grade, tumor size, and number of tumors at diagnosis Table 4 Conditional risk HR* 95% CI Number of Mean number of recur- set model investigating time events/patients rences over 5 years (95% between multiple recurrence at risk CI) events in NMIBC patients treated with TURBT by Smoking status smoking status at diagnosis and  Never smoker 1.00 Ref. 43/99 0.45 (0.28–0.63) after diagnosis  Former smoker 0.71 0.47–1.08 108/254 0.45 (0.33–0.57)  Continuing smoker 1.10 0.72–1.69 116/180 0.64 (0.47–0.81)  Former smoker who started again 0.89 0.56–1.43 108/146 0.82 (0.57–1.06)  Current smoker who quit smoking** 0.85 0.35–2.04 18/19 0.84 (0.10–1.58) *All estimates adjusted for age, sex, stage, grade, tumor size, number of tumors, and re-resection of recur- rent tumor **Smokers who have quit after their first event (n = 2) are also included considerably larger [14]. In another retrospective cohort as lung cancer where this association is stronger, evidence to study, Fleshner et al. concluded that it remained unclear imply a strong, causal relationship between smoking behav- whether smoking cessation at time of diagnosis is benefi- ior after diagnosis and recurrence is still limited [27]; so cial with regard to BC recurrence [15] although Aveyard more prospective research is needed. et al. estimated that the Fleshner study shows a HR of 0.71 Considering the prolonged latency period for the develop- (95% CI 0.48–1.05) when comparing quitters to continuing ment of BC after exposures [2], it is credible that the asso- smokers [26], which is similar to the estimate observed in ciation between altering smoking behavior post-diagnosis the study by Chen et al. Taken together, the limited evidence and likelihood of a first recurrence or multiple recurrences at this point seems to indicate that quitting smoking at or over 5  years is not as strong as the association between closely after diagnosis could reduce risk of recurrence. How- smoking and carcinogenesis. Similarly, epidemiological ever, even across several smoking-related cancer sites such evidence suggests that pre-diagnostic smoking cessation 1 3 Cancer Causes & Control (2018) 29:675–683 681 does not immediately lower the risk of BC [28], also indi- tumors. This theory of “field cancerization” proposes that cating a longer latency period than 5 years. Furthermore, it (pre-)malignant transformation of cells has already occurred is considered that a first BC recurrence is often the result of at different sites across the urothelium, explaining why incomplete resection and/or tumor cell re-implantation, and (changing) smoking exposure will not have a large impact that genuine new tumor formation only plays a more impor- on disease prognosis [36]. tant role in later recurrences [29]. It is therefore reasonable Additionally, given that recent reviews indicate no con- to suggest that, because of the DNA-damaging effects of siderable heterogeneity between studies that do not show an cigarette smoke [30], modifying smoking behavior may only association between environmental tobacco smoke and risk influence later recurrences and possibly those that may occur of BC, it is unlikely that we would have shown any substan- beyond the follow-up period of 5 years reported here. tial association with BC recurrence either [37, 38]. Notwithstanding the results from our study, when consid- Because no substantial association between smoking ering the impact of comorbidities on overall survival in BC status pre-diagnosis and BC recurrence was observed in patients [31] which include several smoking-related diseases adjusted models it is possible that the tumor characteristics [32] and other evidence indicating beneficial and significant associated with BC recurrence (stage, grade, tumor size, results of post-diagnostic smoking cessation in retrospective number of tumors) included as confounders in these models studies [14, 15], it is evident that smoking cessation should overshadow the effects of smoking behavior in determining be encouraged for NMIBC patients at diagnosis. risk of BC recurrence [21] and possible also mortality since It is striking that only 14% of current smokers at diag- no association between quitting smoking after diagnosis and nosis in our sample quit smoking post-diagnosis. There are all-cause or bladder cancer-specific mortality was observed examples of successful smoking cessation interventions in in a large retrospective cohort study [16]. Moreover, since urology [33], and several studies found that when patients current smokers at diagnosis in our cohort have been asso- were diagnosed with BC they were more likely to quit ciated with having a higher stage, higher grade, and larger smoking [34, 35]. Therefore, urologists should continue to tumor size compared to never smokers [39], smoking behav- improve smoking cessation counseling in newly diagnosed ior might play a more crucial role in determining risk of NMIBC patients and be updated on the available tools to recurrence already before diagnosis through promoting unfa- improve smoking cessation figures. Moreover, more inter - vorable tumor characteristics associated with BC recurrence vention clinical research investigating smoking cessation at diagnosis, although in a Dutch cohort of 323 UBC patients programmes in NMIBC patients is warranted. there was only a weak association between smoking inten- sity and increased risk of a more aggressive tumor type [40]. Smoking behavior pre‑diagnosis and exposure to environmental tobacco smoke Strengths and weaknesses Smoking cessation was most beneficial, with regard to Despite the prospective nature of our study there were some reducing the risk of recurrence, the longer before diagnosis limitations restricting the analyses. Due to the relatively it happened compared to continuing smokers. This was the short follow-up of this study, long-term effects of smoking strongest association observed in our study and has been cessation post-diagnosis could not be assessed and the num- observed in other studies as well, although not consistently ber of deaths due to BC in the NMIBC patients within our [12]. Other results were in line with earlier studies inves- cohort was too low for Cox regression analysis. Also, it was tigating smoking status at diagnosis and BC recurrence as not possible to obtain detailed information on adjuvant ther- well, by indicating a slightly increased risk of recurrence apy for all patients, so differences in adjuvant therapy could in NMIBC patients for current smokers compared to never not be considered in the statistical analysis. Additionally, smokers in a meta-analysis [10]. we did not correct for biomarkers of BC recurrence such as Another recent study not included in the aforemen- mutations in the FGFR3 or TP53 genes [41], although they tioned meta-analysis shows similar HRs (HR 1.49, 95% might work together with smoking intensity in predicting CI 0.95–2.33) for current smokers at diagnosis [8]. How- BC outcome [42]. ever, when including this study and our study (data from Furthermore, one of the caveats of using only self- continuing smokers) in the meta-analysis, the pooled HR reported questionnaire data to assess smoking exposure barely changes from 1.27 (95% CI 1.09–1.46) to 1.26 (95% was likely demonstrated in our sample of NMIBC patients. CI 1.12–1.40) [10], indicating a significantly increased risk The large proportion (about 1 in 3) of former smokers pre- of recurrence for current smokers at diagnosis compared to diagnosis who reported to have started smoking again post- never smokers. Possibly, the lack of association for continu- diagnosis is implausible and is probably observed due to ing smokers in this study can be explained through multiple misclassification of either the questionnaire at baseline or synchronous tumors being present at diagnosis in epithelial during follow-up. A high misclassification rate (47%) when 1 3 682 Cancer Causes & Control (2018) 29:675–683 5. Roychowdhury DF, Hayden A, Liepa AM (2003) Health-related comparing self-reported data on smoking behavior to coti- quality-of-life parameters as independent prognostic factors in nine values in blood was also shown in another sample of advanced or metastatic bladder cancer. J Clin Oncol 21:673–678 bladder cancer patients undergoing surveillance [43]. Prefer- 6. Svatek RS, Hollenbeck BK, Holmäng S, Lee R, Kim SP, Stenzl ably, future studies should consider more reliable ways of A et al (2014) The economics of bladder cancer: costs and con- siderations of caring for this disease. Eur Urol 66:253–262. https verifying smoking exposure through biochemical analysis. ://doi.org/10.1016/j.eurur o.2014.01.006 Unfortunately, at the start of the study we did not antici- 7. Hou L, Hong X, Dai M, Chen P, Zhao H, Wei Q et al (2016) pate this small proportion of quitters after diagnosis which Association of smoking status with prognosis in bladder cancer: is why the analysis concerning quitters is underpowered. a meta-analysis. Oncotarget Impact J. https ://doi.org/10.18632 / oncot arget .13606 8. Li HM, Azhati B, Rexiati M, Wang WG, Li XD, Liu Q et al (2016) Impact of smoking status and cumulative smoking exposure on tumor recurrence of non-muscle-invasive bladder cancer. Int Urol Conclusion Nephrol. https ://doi.org/10.1007/s1125 5-016-1441-6 9. 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Journal

Cancer Causes & ControlSpringer Journals

Published: May 30, 2018

References

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