Nicola Fossati1, Daniel P Nguyen2, Quoc-Dien Trinh2, Jesse Sammon2, Akshay Sood2, Alessandro Larcher2, Giorgio Guazzoni2, Francesco Montorsi2, Alberto Briganti2, Mani Menon2, Firas Abdollah2. 1. From Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York; Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Department of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, New York; Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts; Vattikuti Urology Institute and VUI Center for Outcomes Research Analytics and Evaluation, Henry Ford Hospital, Detroit, Michigan; and Department of Urology, Istituto Clinico Humanitas IRCCS, Clinical and Research Hospital, Humanitas University, Rozzano (Milan), Italy. From Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York; Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Department of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, New York; Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts; Vattikuti Urology Institute and VUI Center for Outcomes Research Analytics and Evaluation, Henry Ford Hospital, Detroit, Michigan; and Department of Urology, Istituto Clinico Humanitas IRCCS, Clinical and Research Hospital, Humanitas University, Rozzano (Milan), Italy. 2. From Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York; Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Department of Surgery, Urology Service, Memorial Sloan Kettering Cancer Center, New York, New York; Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts; Vattikuti Urology Institute and VUI Center for Outcomes Research Analytics and Evaluation, Henry Ford Hospital, Detroit, Michigan; and Department of Urology, Istituto Clinico Humanitas IRCCS, Clinical and Research Hospital, Humanitas University, Rozzano (Milan), Italy.
Abstract
BACKGROUND: Approximately 15% of the US population does not have health insurance. The objective of this study was to evaluate the impact of insurance status on tumor characteristics and treatment selection in patients with prostate cancer. MATERIALS AND METHODS: We identified 20,393 patients younger than 65 years with prostate cancer in the 2010-2011 SEER database. Multivariable logistic regression analysis tested the relationship between insurance status and 2 end points: (1) presenting with low-risk prostate cancer at diagnosis and (2) receiving local treatment of the prostate. Locally weighted scatterplot smoothing methods were used to graphically explore the interaction among insurance status, use of local treatment, and baseline risk of cancer recurrence. The latter was defined using the Stephenson nomogram and CAPRA score. RESULTS: Overall, 18,993 patients (93%) were insured, 849 (4.2%) had Medicaid coverage, and 551 (2.7%) were uninsured. At multivariable analysis, Medicaid coverage (odds ratio [OR], 0.67; 95% CI, 0.57, 0.80; P<.0001) and uninsured status (OR, 0.57; 95% CI, 0.46, 0.71; P<.0001) were independent predictors of a lower probability of presenting with low-risk disease. Likewise, Medicaid coverage (OR, 0.72; 95% CI, 0.60, 0.86; P=.0003) and uninsured status (OR, 0.45; 95% CI, 0.37, 0.55; P<.0001) were independent predictors of a lower probability of receiving local treatment. In uninsured patients, treatment disparities became more pronounced as the baseline cancer recurrence risk increased (10% in low-risk patients vs 20% in high-risk patients). CONCLUSIONS: Medicaid beneficiaries and uninsured patients are diagnosed with higher-risk disease and are undertreated. The latter is more accentuated for patients with high-risk prostate cancer. This may seriously compromise the survival of these individuals.
BACKGROUND: Approximately 15% of the US population does not have health insurance. The objective of this study was to evaluate the impact of insurance status on tumor characteristics and treatment selection in patients with prostate cancer. MATERIALS AND METHODS: We identified 20,393 patients younger than 65 years with prostate cancer in the 2010-2011 SEER database. Multivariable logistic regression analysis tested the relationship between insurance status and 2 end points: (1) presenting with low-risk prostate cancer at diagnosis and (2) receiving local treatment of the prostate. Locally weighted scatterplot smoothing methods were used to graphically explore the interaction among insurance status, use of local treatment, and baseline risk of cancer recurrence. The latter was defined using the Stephenson nomogram and CAPRA score. RESULTS: Overall, 18,993 patients (93%) were insured, 849 (4.2%) had Medicaid coverage, and 551 (2.7%) were uninsured. At multivariable analysis, Medicaid coverage (odds ratio [OR], 0.67; 95% CI, 0.57, 0.80; P<.0001) and uninsured status (OR, 0.57; 95% CI, 0.46, 0.71; P<.0001) were independent predictors of a lower probability of presenting with low-risk disease. Likewise, Medicaid coverage (OR, 0.72; 95% CI, 0.60, 0.86; P=.0003) and uninsured status (OR, 0.45; 95% CI, 0.37, 0.55; P<.0001) were independent predictors of a lower probability of receiving local treatment. In uninsured patients, treatment disparities became more pronounced as the baseline cancer recurrence risk increased (10% in low-risk patients vs 20% in high-risk patients). CONCLUSIONS: Medicaid beneficiaries and uninsured patients are diagnosed with higher-risk disease and are undertreated. The latter is more accentuated for patients with high-risk prostate cancer. This may seriously compromise the survival of these individuals.
Authors: Shivanshu Awasthi; Travis Gerke; Vonetta L Williams; Francis Asamoah; Angelina K Fink; Rajesh Balkrishnan; Jong Y Park; Kosj Yamoah Journal: Cancer Control Date: 2019 Jan-Dec Impact factor: 3.302
Authors: Daphne Y Lichtensztajn; John T Leppert; James D Brooks; Sumit A Shah; Weiva Sieh; Benjamin I Chung; Scarlett L Gomez; Iona Cheng Journal: J Natl Compr Canc Netw Date: 2018-11 Impact factor: 12.693