TY - JOUR
AU - Lorusso, Roberto
AB - Dear Editor Cardiac malignancies are rare cancers that manifest as either primary malignant cardiac tumours or as metastases from an extracardiac location1. Approximately 10 per cent of primary cardiac tumours are malignant2. The aim was to assess long-term overall survival differences based on insurance status in patients with malignant cardiac tumours using data from the National Cancer Database (NCDB). This retrospective study included data from the NCDB from 2004 to 2017. Patients with more than one cancer diagnosis over their lifetime were excluded as were those with missing survival time or status. The primary outcome was overall survival and the secondary outcome was operative mortality. Patients were stratified by insurance type. Continuous variables are presented as median (i.q.r.) if not normally distributed, and were compared between groups using the Kruskal–Wallis test. Categorical variables, presented as frequency and percentages, were compared using the χ2 test. All tests were two-sided, and the α level was set at 0.05 for statistical significance. Survival was estimated using Kaplan–Meier curves and compared among groups using the log rank test and univariable Cox model. Independent predictors of mortality were identified by multivariable Cox regression analysis. All statistical analyses were performed using R version 4.0.5 within RStudio. Among 110 991 patients with malignant soft tissue tumours registered in the NCDB throughout the study period, 907 with malignant cardiac tumours were identified; 107 patients were excluded as they had more than one cancer diagnosis over their lifetime, 64 owing to missing survival data, and 37 because their insurance status was unknown (Fig. S1). The study cohort therefore included 699 patients, with a median age of 52 (i.q.r. 37–65) years and 334 women (47.8 per cent) (Table S1). Some 412 patients (58.9 per cent) had private insurance, 243 (34.8 per cent) had governmental insurance, and 44 (6.3 per cent) were uninsured. Overall, the operative mortality rate was 8.5 per cent (11.1, 2.6, 13.9, and 7 per cent in uninsured, Medicaid, Medicare, and private insurance/managed care groups respectively; P = 0.094). At a median follow-up of 64.1 (95 per cent c.i. 60.0 to 79.0) months, compared with the Medicare group, those who were not insured (hazard ratio (HR) 0.64, 95 per cent c.i. 0.44 to 0.94; P = 0.022), had Medicaid (HR 0.72, 0.53 to 0.98; P = 0.036) or with private insurance (HR 0.54, 0.44 to 0.65; P < 0.001) had significantly better survival in univariable Cox regression (Fig. I and Table 1). Based on multivariable Cox regression, higher co-morbidity index (HR 1.92, 1.43 to 2.57; P < 0.001), angiosarcoma (HR 1.34, 1.11 to 1.62; P = 0.002), and stage III–IV cancer (HR 1.35, 1.11 to 1.64; P = 0.003) were associated with shorter survival, whereas private insurance (HR 0.67, 0.52 to 0.87; P = 0.002), year of diagnosis (HR 0.96, 0.94 to 0.98; P < 0.001), surgery (HR 0.43, 0.35 to 0.52; P < 0.001), and chemotherapy (HR 0.60, 0.50 to 0.74, P < 0.001) were associated with better survival. Fig. 1 Open in new tabDownload slide Kaplan–Meier curves for overall survival Dashed lines represent 95 per cent confidence intervals. P < 0.001 (log rank test). Fig. 1 Open in new tabDownload slide Kaplan–Meier curves for overall survival Dashed lines represent 95 per cent confidence intervals. P < 0.001 (log rank test). Table 1 Impact of insurance status on overall survival evaluated in univariable and multivariable analyses . Unadjusted analysis . Adjusted analysis* . Hazard ratio . P . Hazard ratio . P . Medicare 1.00 (reference) 1.00 (reference) Not insured 0.64 (0.44, 0.94) 0.022 1.05 (0.67, 1.63) 0.834 Medicaid 0.72 (0.53, 0.98) 0.036 1.07 (0.73, 1.58) 0.728 Private insurance/managed care 0.54 (0.44, 0.65) < 0.001 0.67 (0.52, 0.87)† 0.002 . Unadjusted analysis . Adjusted analysis* . Hazard ratio . P . Hazard ratio . P . Medicare 1.00 (reference) 1.00 (reference) Not insured 0.64 (0.44, 0.94) 0.022 1.05 (0.67, 1.63) 0.834 Medicaid 0.72 (0.53, 0.98) 0.036 1.07 (0.73, 1.58) 0.728 Private insurance/managed care 0.54 (0.44, 0.65) < 0.001 0.67 (0.52, 0.87)† 0.002 * Adjusted for age, sex, race, median income, county type (urban, metropolitan, rural), Charlson–Deyo Co-morbidity Condition Index, year of diagnosis, histology (others, angiosarcoma), analytical stage group, facility type (academic/integrated, community), surgery, radiation, and chemotherapy. The histology category ‘others’ included leiomyosarcoma (5.3 per cent), fibrosarcoma (5.2 per cent), giant cell sarcoma (4.7 per cent), synovial sarcoma (4.3 per cent), myxosarcoma (3.1 per cent), rhabdomyosarcoma (2.9 per cent), osteosarcoma (2.6 per cent), malignant fibrous histiocytoma (1.8 per cent), liposarcoma (0.7 per cent), malignant peripheral nerve sheath tumours (0.6 per cent), Ewing sarcoma (0.3 per cent), and others/unclassified (25.8 per cent). Surgery was undertaken in 420 patients (60.1 per cent), whereas chemotherapy and radiotherapy were administered to 352 (50.4 per cent) and 121 (17.3 per cent) respectively. †Results were consistent when a mixed-effect Cox regression with PUF_FACILITY_ID was used as a random model to account for hospital volume (HR 0.67, 0.52 to 0.87; P = 0.002). Open in new tab Table 1 Impact of insurance status on overall survival evaluated in univariable and multivariable analyses . Unadjusted analysis . Adjusted analysis* . Hazard ratio . P . Hazard ratio . P . Medicare 1.00 (reference) 1.00 (reference) Not insured 0.64 (0.44, 0.94) 0.022 1.05 (0.67, 1.63) 0.834 Medicaid 0.72 (0.53, 0.98) 0.036 1.07 (0.73, 1.58) 0.728 Private insurance/managed care 0.54 (0.44, 0.65) < 0.001 0.67 (0.52, 0.87)† 0.002 . Unadjusted analysis . Adjusted analysis* . Hazard ratio . P . Hazard ratio . P . Medicare 1.00 (reference) 1.00 (reference) Not insured 0.64 (0.44, 0.94) 0.022 1.05 (0.67, 1.63) 0.834 Medicaid 0.72 (0.53, 0.98) 0.036 1.07 (0.73, 1.58) 0.728 Private insurance/managed care 0.54 (0.44, 0.65) < 0.001 0.67 (0.52, 0.87)† 0.002 * Adjusted for age, sex, race, median income, county type (urban, metropolitan, rural), Charlson–Deyo Co-morbidity Condition Index, year of diagnosis, histology (others, angiosarcoma), analytical stage group, facility type (academic/integrated, community), surgery, radiation, and chemotherapy. The histology category ‘others’ included leiomyosarcoma (5.3 per cent), fibrosarcoma (5.2 per cent), giant cell sarcoma (4.7 per cent), synovial sarcoma (4.3 per cent), myxosarcoma (3.1 per cent), rhabdomyosarcoma (2.9 per cent), osteosarcoma (2.6 per cent), malignant fibrous histiocytoma (1.8 per cent), liposarcoma (0.7 per cent), malignant peripheral nerve sheath tumours (0.6 per cent), Ewing sarcoma (0.3 per cent), and others/unclassified (25.8 per cent). Surgery was undertaken in 420 patients (60.1 per cent), whereas chemotherapy and radiotherapy were administered to 352 (50.4 per cent) and 121 (17.3 per cent) respectively. †Results were consistent when a mixed-effect Cox regression with PUF_FACILITY_ID was used as a random model to account for hospital volume (HR 0.67, 0.52 to 0.87; P = 0.002). Open in new tab The results were consistent when a mixed-effect Cox regression with hospital identifier as a random model was used to account for clustering (HR for private insurance 0.67, 0.52 to 0.87; P = 0.002). In this analysis of 699 patients with malignant cardiac tumours at a median follow-up of 64.1 months, higher co-morbidity index, angiosarcoma, and stage III–IV cancer were associated with shorter survival, whereas private insurance, recent year of diagnosis, treatment by surgery, and chemotherapy were associated with better survival. The main limitation of the study lies in the possibility of unknown confounder bias owing to its retrospective nature. A recent study3 showed a significant increase in early mortality after cardiac valve surgery in uninsured patients, and those with Medicaid or Medicare compared with patients who had private insurance. Conflicting opinions exist on the impact of insurance status on different outcomes among various cancers4. Although a previous series5 reported that short-term mortality in major surgical operations was affected by insurance status, the difference was not statistically significant in patients with cardiac tumours. This study provides increased awareness of the survival disparity according to insurance status among patients with primary malignant cardiac tumours. Further studies are warranted to explore this association in depth. Supplementary material Supplementary material is available at BJS online. References 1 Taguchi S. Comprehensive review of the epidemiology and treatments for malignant adult cardiac tumors . Gen Thorac Cardiovasc Surg 2018 ; 66 : 257 – 262. Google Scholar Crossref Search ADS PubMed WorldCat 2 Rahouma M , Arisha MJ, Elmously A, El-Sayed Ahmed MM, Spadaccio C, Mehta K et al. Cardiac tumors prevalence and mortality: a systematic review and meta-analysis . Int J Surg Lond Engl 2020 ; 76 : 178 – 189. Google Scholar Crossref Search ADS WorldCat 3 Hoyler MM , Feng TR, Ma X, Rong LQ, Avgerinos DV, Tam CW et al. Insurance status and socioeconomic factors affect early mortality after cardiac valve surgery . J Cardiothorac Vasc Anesth 2020 ; 34 : 3234 – 3242. Google Scholar Crossref Search ADS PubMed WorldCat 4 Yang J , Fu Z, Du L, He X, Li X, Chen J. Time to surgery in patients with breast cancer during the COVID-19 pandemic . Br J Surg 2020 ; 107 : e419 – e421. Google Scholar Crossref Search ADS PubMed WorldCat 5 LaPar DJ , Bhamidipati CM, Mery CM, Stukenborg GJ, Jones DR, Schirmer BD et al. Primary payer status affects mortality for major surgical operations . Ann Surg 2010 ; 252 : 544 – 551. Google Scholar Crossref Search ADS PubMed WorldCat © The Author(s) 2021. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. 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TI - Association between insurance status and survival among patients with malignant cardiac tumours
JF - British Journal of Surgery
DO - 10.1093/bjs/znab423
DA - 2021-12-20
UR - https://www.deepdyve.com/lp/oxford-university-press/association-between-insurance-status-and-survival-among-patients-with-Gk1CLLa0co
SP - e24
EP - e25
VL - 109
IS - 2
DP - DeepDyve
ER -