Validation of a Case-Finding Algorithm for Identifying Patients with Non-small Cell Lung Cancer (NSCLC) in Administrative Claims Databases

Turner, Ralph M.; Chen, Yen‐Wen; Fernandes, Ancilla W.

doi:10.3389/fphar.2017.00883

Cited by 22 publications

(28 citation statements)

References 20 publications

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“…This study aimed to examine patient characteristics and treatment patterns among adult patients newly diagnosed with metastatic NSCLC through two RWD sources: health insurance claims data and US nationwide EHRs. 6 (Appendix) Lung cancer drugs included in the study (adapted from Turner et al [13], with inclusion of newly approved drugs and relevant HCPCS codes); (4) with continuous health plan enrollment or active EHR records for at least 6 months before and at least 1 month after the systemic treatment initiation (patients who were deceased within 1 month from systemic treatment initiation were kept in the cohorts); (5) with age ≥ 18 years and known sex at the time of systemic treatment initiation; (6) without any record of receiving SCLC-specific treatments (topotecan, cyclophosphamide, doxorubicin, vincristine, temozolomide, ifosfamide, bendamustine at any time, or platinum + topoisomerase inhibitor combination [cisplatin/carboplatin + etoposide/ irinotecan] as the first-line regimen). Patients were followed from the earliest systemic treatment date until a censoring event (i.e., end of continuous health plan enrollment or active EHR, death, or end of data availability [30 September 2020]).…”

Section: Study Cohortsmentioning

confidence: 99%

Comparison Between Health Insurance Claims and Electronic Health Records (EHRs) for Metastatic Non-small-cell Lung Cancer (NSCLC) Patient Characteristics and Treatment Patterns: A Retrospective Cohort Study

Choi

Zhang

Tyczynski

2021

Drugs - Real World Outcomes

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Background The clinical landscape in non-small-cell lung cancer (NSCLC) treatment has rapidly evolved in recent years. Real-world data (RWD) can provide insights into current clinical practice. Objective This study examined the patient characteristics and treatment patterns of patients with metastatic NSCLC using RWD sources. Methods This was a retrospective cohort study using health insurance claims and electronic health records (EHRs). Adult patients treated for metastatic NSCLC during the period 2017 to September 2020 were followed from the earliest treatment date until a censoring event. Results The claims cohort included 7917 patients with a mean age of 70 years and a mean follow-up period of 373 days. The EHR cohort included 7087 patients with a mean age of 67 years and a mean follow-up period of 362 days. The five most common first-line therapies (LoT1) were the same for both cohorts: carboplatin + paclitaxel, pembrolizumab, carboplatin + pemetrexed + pembrolizumab, cisplatin + pemetrexed, and nivolumab. Mean LoT1 durations were 146 and 147 days in the claims and EHR cohorts, respectively. For patients who received a second LoT (LoT2), the five most common LoT2 were also the same in both cohorts: durvalumab, nivolumab, pembrolizumab, carboplatin + pembrolizumab + pemetrexed, and carboplatin + pemetrexed. Mean LoT2 durations were 157 and 158 days in the claims and EHR cohorts, respectively. Conclusions LoTs between the claims and EHR cohorts were comparable and showed similar treatment patterns. Traditional platinum-containing chemotherapy was most common in LoT1, whereas programmed cell death protein-1 inhibitors became the most common choices in LoT2. Our findings suggest that RWD can reliably provide up-to-date insight into current treatment modalities and indicate that new clinical evidence is rapidly adopted in patients with NSCLC.

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Section: Study Cohortsmentioning

confidence: 99%

Comparison Between Health Insurance Claims and Electronic Health Records (EHRs) for Metastatic Non-small-cell Lung Cancer (NSCLC) Patient Characteristics and Treatment Patterns: A Retrospective Cohort Study

Choi

Zhang

Tyczynski

2021

Drugs - Real World Outcomes

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“…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

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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.

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“…Medical claims data from health insurance systems constitute a potential means for identification of cancer cases, and the performance of this method has been evaluated in several previous studies (4-13). For example, Medicare claims were reported to be accurate in capturing cases of breast, colorectal and endometrial cancer (6,8).…”

Section: Introductionmentioning

confidence: 99%

“…For example, Medicare claims were reported to be accurate in capturing cases of breast, colorectal and endometrial cancer (6,8). The HealthCore Integrated Research Database was found to be sensitive in identifying patients with non-small cell lung cancer (13). For these studies, effective identification of cancer cases can be guaranteed by qualified and accurate diagnostic information in medical claims.…”

Section: Introductionmentioning

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

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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.

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Validation of a Case-Finding Algorithm for Identifying Patients with Non-small Cell Lung Cancer (NSCLC) in Administrative Claims Databases

Cited by 22 publications

References 20 publications

Comparison Between Health Insurance Claims and Electronic Health Records (EHRs) for Metastatic Non-small-cell Lung Cancer (NSCLC) Patient Characteristics and Treatment Patterns: A Retrospective Cohort Study

Comparison Between Health Insurance Claims and Electronic Health Records (EHRs) for Metastatic Non-small-cell Lung Cancer (NSCLC) Patient Characteristics and Treatment Patterns: A Retrospective Cohort Study

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

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

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