Bladder Cancer Survivors Who Do Not Smoke Have Better Longitudinal Health-Related Quality of Life Measures: An Assessment of the Comparative Effectiveness and Survivorship Health in Bladder Cancer (CEASE-BC) Study.

PURPOSE: Cigarette smoking is the most common risk factor for the development of bladder cancer (BC), yet there is a paucity of data characterizing the relationship between smoking status and longitudinal health-related quality of life (HRQoL) outcomes in patients with BC. We examined the association between smoking status and HRQoL among patients with BC. MATERIALS AND METHODS: Data were sourced from a prospective, longitudinal study open between 2014 and 2017, which examined HRQoL in patients aged ≥ 18 years old diagnosed with BC across North Carolina. The QLQ-C30 (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core instrument) was administered at 3, 12, and 24 months after BC diagnosis. Our primary exposure of interest was current smoking status. Linear regression using generalized estimating equations was used to analyze the relationship between smoking status and various domains of the QLQ-C30. RESULTS: A total of 154 patients enrolled in the study. Eighteen percent were classified as smoking at 3 months from diagnosis, and packs per day ranged from < 0.5 to 2. When controlling for time from diagnosis, demographic covariates, cancer stage, and treatment type, mean differences for physical function (7.4), emotional function (5.6), and fatigue measures (-8.2) were significantly better for patients with BC who did not smoke. CONCLUSIONS: Patients with BC who do not smoke have significantly better HRQoL scores in the domains of physical function, emotional function, and fatigue. These results underscore the need to treat smoking as an essential component of BC care.

Diversity, equity, and inclusion in genitourinary clinical trials leading to FDA novel drug approval: An assessment of the FDA center for drug evaluation and research drug trials snapshot.

To determine the distribution of race and ethnicity among genitourinary oncology trial participants leading to FDA approval of novel molecular entities/biologics. Secondarily, we evaluated whether the proportion of Black participants in clinical trials increased over time. We quired the FDA Center for Drug Evaluation and Research Drug Trials Snapshot (DTS) between 2015 and 2020 for urologic oncology clinical trials leading to FDA approval of novel drugs. Enrollment data was stratified by race and ethnicity. Cochran-Armitage Trend tests were used to examine changes in Black patient participation over years. Nine clinical trials were identified that led to FDA approval of 5 novel molecular entities for prostate and 4 molecular entities for urothelial carcinoma treatment. Trials for prostate cancer included 5202 participants of which 69.8% were White, 4.0% Black, 11.0% Asian, 3.6% Hispanic, <1% American Indian/Alaska Native or Native Hawaiian/Pacific Islander, 3% other. Trials in urothelial carcinoma had 704 participants of which 75.1% were male, 80.8% White, 2.3% Black, 2.4% Hispanic, <1% American Indian/Alaska Native or Native Hawaiian/Pacific Islander, 5% other. Black participation rates over time did not change for urothelial (P = 0.59) or the combined cancer cohort (P = 0.29). Prostate cancer enrollment trends among Black participant declined over time (P = 0.03). Participants in genitourinary clinical trials leading to FDA approval of novel drugs are overwhelmingly white. Involving stakeholders who represent the needs and interests of underrepresented populations in the design and implementation of clinical trials of novel agents may be a strategy to increase diversity, equity, and inclusion among genitourinary clinical trials.

Non-oncology clinical trial engagement in a nationally representative sample: Identification of motivators and barriers.

BACKGROUND: Enrollment in non-oncology clinical trials is often challenging and social determinants that may serve as motivators or barriers to clinical trial enrollment are largely unexplored. We sought to assess engagement in non-oncology clinical trials with a focus on social determinants of health as barriers or motivators toward participation. METHODS: A cross-sectional analysis of non-cancer respondents was conducted using the Health Information National Trends Survey (HINTS) administered in 2020. Our analytic cohort was comprised of respondents with no reported history of cancer. Our primary outcome of interest was trial engagement defined as receiving an invitation to participate in a clinical trial. Secondary outcomes included participation in a clinical trial and reported motivators and barriers to clinical trial participation. RESULTS: A total of 3113 respondents with no reported history of cancer were included. Overall, 8.1% of respondents reported being invited to participate in a clinical trial. Amongst those invited to participate, 47.7% reported participating in a clinical trial. Respondents reported that clinical trial participation was motivated "somewhat" or "a lot" by "wanting to get better" (80.5%), "helping other people" (61.4%), "physician encouragement" (60.6%), "getting a chance to try new care" (60.2%), "family friend encouragement" (54.2%), or "getting paid" (50.0%). Overall, 82.5% of all respondents "don't know anything" or have "a little knowledge" about clinical trials. Reported barriers to clinical trial participation including getting transportation, childcare or paid time off work (48.4%) and standard of care not covered by insurance (62.0%) influenced the decision to participate "somewhat" or "a lot." CONCLUSION: Amongst a nationally representative sample, non-oncology clinical trial invitation is low, but participation amongst those invited is nearly 50%. This highlights the need for clinician engagement in clinical trials. Identifying modifiable social determinants of non-oncologic clinical trial participation may help promote improved engagement.

Total Medicare Costs Associated With Diagnosis and Treatment of Prostate Cancer in Elderly Men.

Importance: Localized prostate cancer diagnosis and treatment among elderly men who are not likely to benefit represents a potential source of low-value health care services. Objective: To quantify the costs to the Medicare program associated with detection and treatment of prostate cancer among elderly men in the United States. Design, Setting, and Participants: This nationwide, population-based, retrospective cohort study uses the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database to identify men 70 years or older diagnosed with localized prostate cancer between 2004 and 2007 and to ascertain Medicare costs associated with diagnosis and workup, treatment, follow-up, and morbidity management of the disease. National Medicare costs were estimated using per-person costs, stage-adjusted prostate cancer incidence rates by age from SEER 2007 through 2011, and 2010 Census population estimates by age. Main Outcomes and Measures: Estimated costs to the Medicare program overall, and in each (mutually exclusive) category related to diagnosis and workup, treatment, follow-up, and morbidity management. Results: This nationwide, population-based, retrospective cohort study included 49 692 men with nonmetastatic prostate cancer from the SEER-Medicare database (all participants were 70 years or older; 25 981 [52.3%] were 76 years or older). The median per-patient cost within 3 years after prostate cancer diagnosis was $14 453 (interquartile range [IQR], $4887-$27 899). The majority of this cost was attributable to treatment costs (median, $10 558; IQR, $1990-$23 718). Patients with a Gleason score of 6 or lower who pursued initial conservative management (no treatment within 12 months of diagnosis) had a 3-year median total cost of $1914 per patient. The estimated total 3-year cost to the Medicare program associated with the annual detection of prostate cancer in men 70 years or older is approximately $1.2 billion. Increasing active surveillance use in those with Gleason score of 6 or lower could reduce this cost by $320 million. Conclusions and Relevance: There is substantial cost to the Medicare program associated with the diagnosis and treatment of localized prostate cancer among elderly men in the United States, despite the fact that these men are unlikely to die of prostate cancer. The majority of costs are related to treatment. Reducing provision of low-value health care services among this patient population could result in significant health care savings.

Comparative Effectiveness of Prostate Cancer Treatment Options: Limitations of Retrospective Analysis of Cancer Registry Data.

PURPOSE: Retrospective analyses of cancer registry and institutional data have consistently found better survival after radical prostatectomy versus radiation therapy, which contrasts with findings from a randomized trial. This is likely because of the inability of retrospective studies to fully account for comorbidity differences across treatment groups because of the lack of detailed data in the registries. We use a unique population-based data set with detailed data regarding comorbidities and functional limitations to assess whether this can provide valid comparisons of survival across prostate cancer treatment groups. METHODS AND MATERIALS: The Surveillance, Epidemiology, and End Results (SEER)-Medicare Health Outcomes Survey (MHOS) data set results from a linkage between the SEER database and the MHOS database, which includes detailed information regarding patient-reported comorbidity and functional limitations. We analyzed 3102 patients with prostate cancer in SEER-MHOS and used latent class analysis to identify the healthiest group with minimal comorbidity burden and functional limitations. Among the healthiest group, we examined overall survival across treatments using the Kaplan-Meier method. RESULTS: Three distinct health groups were identified using latent class analysis; the healthiest group comprised 57% of the cohort and had a 10-year overall survival of 67%. Other health groups had higher rates of comorbidities or functional limitations. Among the healthiest group, 10-year overall survival differed across treatment groups: no local treatment (55%), external beam radiation therapy (69%), brachytherapy (76%), and radical prostatectomy (85%). Survival curves for the 3 treated groups separated at 4 years of follow-up. CONCLUSIONS: Despite the detailed health status information available in SEER-MHOS, our retrospective analysis could not fully account for patient selection biases across prostate cancer treatment groups. These findings highlight an important limitation of retrospective studies using population-based data sets and serve as a reminder to interpret results with caution.

Ascertainment of postprostatectomy radiotherapy for prostate cancer in the Surveillance, Epidemiology, and End Results database.

BACKGROUND: Surveillance, Epidemiology, and End Results (SEER) data are frequently used to examine receipt of adjuvant radiotherapy (RT), but to the authors' knowledge the accuracy of data regarding second-course treatments is unknown. METHODS: Using SEER-Medicare-linked data, the authors identified a cohort of men who underwent radical prostatectomy for localized prostate cancer with indications for RT due to adverse pathologic risk factors. Receipt of RT was compared between the SEER database and Medicare claims, with the latter considered to be the "gold standard." Multivariable logistic regression was used to assess factors associated with ascertainment of RT in SEER. RESULTS: A total of 3842 men were analyzed, 749 of whom were found to have Medicare claims for RT within 1 year of undergoing prostatectomy. SEER ascertainment of postprostatectomy RT was 56% overall: 76% among patients who received RT within 2 months of prostatectomy, 73% among patients who received RT between 2 to 4 months after prostatectomy, 63% among patients who received RT between 4 to 6 months after prostatectomy, 44% among patients who received RT between 6 to 8 months after prostatectomy, and 21% among patients who received RT between 8 to 12 months after prostatectomy. On multivariable analysis, increasing time from prostatectomy to RT was found to be significantly associated with decreased SEER ascertainment (odds ratio, 0.70 per month; P<.001). There also was variation noted by SEER region and urban/rural locale. CONCLUSIONS: SEER underascertains the receipt of postprostatectomy RT compared with Medicare claims, and the magnitude of the underascertainment increases with longer time between prostatectomy and RT. These findings have direct implications for the use of SEER data alone to assess patterns of care and guideline concordance for second-course treatment. Cancer 2016;122:3069-3074. © 2016 American Cancer Society.

Adherence to multiple medications prescribed for a chronic disease: a methodological investigation.

BACKGROUND: Many patients receive multiple medications for the treatment of a disease. While monitoring adherence is important, a composite measure of adherence is useful for estimating adherence to multiple medications in these patients. There are multiple ways to compute composite estimates of adherence to multiple medications, including (a) 80% of days covered by at least 1 medication ("at least 1"); (b) 80% of days covered by both medications ("both"); (c) 80% of days covered by each medication measured separately ("all"); and (d) computing an average of the individual medication adherence estimates ("average"). Comparison of adherence rates to individual medications and that of composite estimates are important for intervention decisions and effective disease management.  OBJECTIVES: To (a) examine adherence to multiple medications prescribed for a disease; (b) estimate composite adherence to multiple medications prescribed for a disease; and (c) determine the rate of differential classification of a patient being adherent as is estimated by different available algorithms.   METHODS: A retrospective cohort study was designed using 2002-2003 MarketScan Commercial Claims and Encounters data. To be included in the cohort, patients had to be less than aged 65 years and had to have separate prescriptions filled for 2 classes of diabetes medications (i.e., any sulfonylurea [SU] and any thiazolidinedione [TZD]) at least once; patients taking other diabetic medications over the observation period were excluded. Adherence was measured by proportion of days covered (PDC) over periods of 90 days (8 quarters total) and cumulatively over the 2-year study period. For some composite adherence estimates, patients were considered adherent if PDC ≥ 80%. Survival curves using the life-table method were constructed to compare the time until PDC became less than 80% as estimated by the 3 different categorical composite measures. RESULTS: A total of 6,043 patients were included in the analysis. Across the 8 quarters under consideration, the average PDC estimates ranged between 69.8%-84.2% for SUs and 70.3%-85.6% for TZDs. The mean composite PDC based on the average algorithm varied between 69.4% and 84.9% when measured over each quarter or cumulatively. Similarly, the rates of composite adherence ranged from 74.5% to 88.2%, 46.4% to 61.2%, and 47.7% to 62.9% for the "at least 1," "both," and "all" methods, respectively. Many subjects were classified as adherent by 1 composite dichotomous measure but not by all 3 dichotomous measures (i.e., "all," "at least 1," and "both"); of these patients, 30.6%-38.2% were classified differently as to their adherence status over different quarters by different measures. Survival curves of categorical composite measures were different (P less than 0.05) from one another. "At least 1" identified more patients as persistent and showed a much slower decline than did the "all" or "both" approaches.  CONCLUSIONS: Subjects were found to have a level of adherence-as estimated by individual medication adherence and composite adherence metrics-for multiple medications prescribed for a disease that, while not optimal from the perspective of patient care, was not entirely poor. In addition, composite estimates of adherence considerably varied depending on algorithms used. Most importantly, a large number of patients appeared to be subject to inconsistent classification based on adherence measurement algorithm. Adherence estimates produced by different composite measurement approaches give rise to difficulty in consistent interpretation, which may be detrimental to appropriate patient care decision making.