Validation of an Algorithm for Claims-based Incidence of Prostate Cancer

Parlett, Lauren E.; Beachler, Daniel C.; Lanes, Stephan; Hoover, Robert N.; Cook, Michael B.

doi:10.1097/ede.0000000000001007

Cited by 12 publications

(14 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The HealthCore Integrated Research Database (HIRD) is a repository of administrative claims beginning in 2006 with linked medical, pharmacy, and eligibility data for approximately 59 million researchable covered lives (at the time of this study) with a median continuous membership of 3 years enrolled in 14 commercial health plans across the United States (9,10). From the HIRD, we selected men ages 30 years or greater with medical and pharmacy coverage who were newly dispensed a TT prescription (see Supplementary Table S1 for codes) during January 1, 2007, to July 31,2015.…”

Section: Methodsmentioning

confidence: 99%

Testosterone Therapy in Relation to Prostate Cancer in a U.S. Commercial Insurance Claims Database

Cook¹,

Beachler

Parlett³

et al. 2020

Cancer Epidemiology, Biomarkers &Amp; Prevention

Self Cite

View full text Add to dashboard Cite

Background: We conducted a study to assess whether testosterone therapy (TT) alters prostate cancer risk using a large U.S. commercial insurance research database.Methods: From the HealthCore Integrated Research Database (HIRD), we selected men ages 30 years or greater who were new users of TT during 2007 to 2015. We selected two comparison groups: (i) unexposed (matched 10:1) and (ii) new users of phosphodiesterase type 5 inhibitor (PDE5i). Incident prostate cancer was defined as diagnosis of prostate cancer within 4 weeks following prostate biopsy. Propensity scores and inverse probability of treatment weights were used in Poisson regression models to estimate adjusted incidence rates, incidence rate ratios (IRR), and 95% confidence intervals (CI). Subgroup analyses included stratification by prostate cancer screening, hypogonadism, and follow-up time.Results: The adjusted prostate cancer IRR was 0.77 (95% CI, 0.68-0.86) when comparing TT with the unexposed group and 0.85 (95% CI, 0.79-0.91) in comparison with the PDE5i group. Inverse associations between TT and prostate cancer were observed in a majority of subgroup analyses, although in both comparisons estimates generally attenuated with increasing time following initial exposure. Among TT users, duration of exposure was not associated with prostate cancer.Conclusions: Men who received TT did not have a higher rate of prostate cancer compared with the unexposed or PDE5i comparison groups. The inverse association between TT and prostate cancer could be the result of residual confounding, contraindication bias, or undefined biological effect.Impact: This study suggests that limited TT exposure does not increase risk of prostate cancer in the short term.

show abstract

Section: Methodsmentioning

confidence: 99%

Testosterone Therapy in Relation to Prostate Cancer in a U.S. Commercial Insurance Claims Database

Cook¹,

Beachler

Parlett³

et al. 2020

Cancer Epidemiology, Biomarkers &Amp; Prevention

Self Cite

View full text Add to dashboard Cite

show abstract

“…PBCR serves as the gold standard for determination of incident cancer cases (29). In previous studies, the accuracy of identification of cancer cases using medical claims in the health insurance system has been evaluated in several other countries, such as the USA (sensitivity 91%, PPV 82%, prostate cancer) (30), Canada (sensitivity 87%, PPV 79%, pancreatic cancer) (31), and Japan (sensitivity 90%, PPV 87%, breast cancer) (32). For areas not covered by PBCRs in China, claims data have the potential to provide a basis for cancer surveillance, but the accuracy of this method must first be evaluated.…”

Section: Discussionmentioning

confidence: 99%

Identification of cancer patients using claims data from health insurance systems: A real-world comparative study

Tian

et al. 2019

Chinese Journal of Cancer Research

View full text Add to dashboard Cite

ObjectiveTo evaluate the accuracy of identifying cancer patients by use of medical claims data in a health insurance system in China, and provide the basis for establishing the claims-based cancer surveillance system in China.MethodsWe chose Hua County, Henan Province as the study site, and randomly selected 300 and 1,200 qualified inpatient electronic medical records (EMRs) as well as the New Rural Cooperative Medical Scheme (NCMS) claims records for cancer patients in Hua County People’s Hospital (HCPH) and Anyang Cancer Hospital (ACH) in 2017. Diagnostic information for NCMS claims was evaluated on an individual level, and sensitivity and positive predictive value (PPV) were calculated taking the EMRs as the gold standard.ResultsThe sensitivity of NCMS was 95.2% (93.8%−96.3%) and 92.0% (88.3%−94.8%) in ACH and HCPH, respectively. The PPV of the NCMS was 97.8% (96.7%−98.5%) in ACH and 89.0% (84.9%−92.3%) in HCPH. Overall, the weighted and combined sensitivity and PPV of NCMS in Hua County was 93.1% and 92.1%, respectively. Significantly higher sensitivity and PPV in identifying patients with common cancers than non-common cancers were detected in HCPH and ACH separately (P<0.01).ConclusionsIdentification of cancer patients by use of the NCMS is accurate on individual level, and it is therefore feasible to conduct claims-based cancer surveillance in areas not covered by cancer registries in China.

show abstract

“…For example, integrated data allow the inclusion of important clinical factors when analyzing health care utilization and costs, as recorded in claims [13]. Such integrated observational data sets have also been used to generate predictive algorithms to better identify patients with cancer [14][15][16][17] and their disease characteristics [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Data Integration to Improve Real-world Health Outcomes Research for Non–Small Cell Lung Cancer in the United States: Descriptive and Qualitative Exploration

et al. 2021

View full text Add to dashboard Cite

Background The integration of data from disparate sources could help alleviate data insufficiency in real-world studies and compensate for the inadequacies of single data sources and short-duration, small sample size studies while improving the utility of data for research. Objective This study aims to describe and evaluate a process of integrating data from several complementary sources to conduct health outcomes research in patients with non–small cell lung cancer (NSCLC). The integrated data set is also used to describe patient demographics, clinical characteristics, treatment patterns, and mortality rates. Methods This retrospective cohort study integrated data from 4 sources: administrative claims from the HealthCore Integrated Research Database, clinical data from a Cancer Care Quality Program (CCQP), clinical data from abstracted medical records (MRs), and mortality data from the US Social Security Administration. Patients with lung cancer who initiated second-line (2L) therapy between November 01, 2015, and April 13, 2018, were identified in the claims and CCQP data. Eligible patients were 18 years or older and received atezolizumab, docetaxel, erlotinib, nivolumab, pembrolizumab, pemetrexed, or ramucirumab in the 2L setting. The main analysis cohort included patients with claims data and data from at least one additional data source (CCQP or MR). Patients without integrated data (claims only) were reported separately. Descriptive and univariate statistics were reported. Results Data integration resulted in a main analysis cohort of 2195 patients with NSCLC; 2106 patients had CCQP and 407 patients had MR data. The claims-only cohort included 931 eligible patients. For the main analysis cohort, the mean age was 62.1 (SD 9.27) years, 48.56% (1066/2195) were female, the median length of follow-up was 6.8 months, and for 37.77% (829/2195), death was observed. For the claims-only cohort, the mean age was 66.6 (SD 12.69) years, 52.1% (485/931) were female, the median length of follow-up was 8.6 months, and for 29.3% (273/931), death was observed. The most frequent 2L treatment was immunotherapy (1094/2195, 49.84%), followed by platinum-based regimens (472/2195, 21.50%) and single-agent chemotherapy (441/2195, 20.09%); mean duration of 2L therapy was 5.6 (SD 4.9, median 4) months. We describe challenges and learnings from the data integration process, and the benefits of the integrated data set, which includes a richer set of clinical and outcome data to supplement the utilization metrics available in administrative claims. Conclusions The management of patients with NSCLC requires care from a multidisciplinary team, leading to a lack of a single aggregated data source in real-world settings. The availability of integrated clinical data from MRs, health plan claims, and other sources of clinical care may improve the ability to assess emerging treatments.

show abstract

Validation of an Algorithm for Claims-based Incidence of Prostate Cancer

Cited by 12 publications

References 16 publications

Testosterone Therapy in Relation to Prostate Cancer in a U.S. Commercial Insurance Claims Database

Testosterone Therapy in Relation to Prostate Cancer in a U.S. Commercial Insurance Claims Database

Identification of cancer patients using claims data from health insurance systems: A real-world comparative study

Data Integration to Improve Real-world Health Outcomes Research for Non–Small Cell Lung Cancer in the United States: Descriptive and Qualitative Exploration

Contact Info

Product

Resources

About