scholarly journals Real-World Utilization of Target- and Immunotherapies for Lung Cancer: A Scoping Review of Studies Based on Routinely Collected Electronic Healthcare Data

2021 ◽  
Vol 18 (14) ◽  
pp. 7679
Author(s):  
Andrea Spini ◽  
Giulia Hyeraci ◽  
Claudia Bartolini ◽  
Sandra Donnini ◽  
Pietro Rosellini ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Drug Utilization ◽  
Scoping Review ◽  
Medical Records ◽  
Cancer Registries ◽  
Small Cell ◽  
Administrative Claims ◽  
Administrative Claim Data ◽  
Healthcare Data ◽  
Data Source

Routinely collected electronic healthcare data (rcEHD) have a tremendous potential for enriching pre-marketing evidence on target- and immunotherapies used to treat lung cancer (LC). A scoping review was performed to provide a structured overview of available rcEHD-based studies on this topic and to support the execution of future research by facilitating access to pertinent literature both for study design and benchmarking. Eligible studies published between 2016 and 2020 in PubMed and ISI Web of Science were searched. Data source and study characteristics, as well as evidence on drug utilization and survival were extracted. Thirty-two studies were included. Twenty-six studies used North American data, while three used European data only. Thirteen studies linked ≥1 data source types among administrative/claims data, cancer registries and medical/health records. Twenty-nine studies retrieved cancer-related information from medical records/cancer registries and 31 studies retrieved information on drug utilization or survival from medical records or administrative/claim data. Most part of studies concerned non-small-cell-LC patients (29 out of 32) while none focused on small-cell-LC. Study cohorts ranged between 85 to 81,983 patients. Only two studies described first-line utilization of immunotherapies. Results from this review will serve as a starting point for the execution of future rcEHD-based studies on innovative LC pharmacotherapies.

scholarly journals A text-mining approach to obtain detailed treatment information from free-text fields in population-based cancer registries: A study of non-small cell lung cancer in California

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0212454 ◽  
Author(s):  
Frances B. Maguire ◽  
Cyllene R. Morris ◽  
Arti Parikh-Patel ◽  
Rosemary D. Cress ◽  
Theresa H. M. Keegan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Text Mining ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cancer Registries ◽  
Population Based ◽  
Small Cell ◽  
Free Text ◽  
Small Cell Lung ◽  
Treatment Information

scholarly journals Incorporation of EGFR mutation status into M descriptor of new TNM classification influences survival curves in non-small cell lung cancer patients

2019 ◽  
Vol 53 (4) ◽  
pp. 453-458
Author(s):  
Karmen Stanic ◽  
Nina Turnsek ◽  
Martina Vrankar
Keyword(s):  
Lung Cancer ◽  
Medical Records ◽  
Disease Burden ◽  
Egfr Mutation ◽  
Tnm Classification ◽  
Small Cell ◽  
Egfr Mutations ◽  
Small Cell Lung ◽  
Mutation Status ◽  
Nsclc Patients

Abstract Background The 8th edition of tumor node metastasis (TNM) staging system for lung cancer introduced a revision of M descriptor. The limitation of new classification to predict prognosis is its focus on anatomical extent of the disease only. Information on molecular status of the tumor significantly influences treatment response and survival; however, data addressing this issue is scarce. This report points to the impact of epidermal growth factor receptor (EGFR) mutation in non-small cell lung cancer (NSCLC) patients on survival in view of new M descriptors of TNM classification system. Patients and methods Medical records of 479 consecutive metastatic NSCLC patients treated between 2009 and 2011, all tested for EGFR mutations, were retrospectively reviewed. For 355 patients medical records included sufficient information to be appropriately categorized into one of the new subgroups according to the M descriptor in 8th TNM classification, of those 89 (25.1%) patients harboured EGFR mutations (EGFR-m). Results Median overall survival (mOS) of EGFR-m patients was significantly longer than mOS of patients without EGFR mutations (20.6 months vs. 8.3 months, p < 0.001). Patients with limited disease burden (M1b sub-group) had the longest mOS among EGFR wild type patients (EGFR-wt) and also among EGFR-m patients, 14.4 months and 39.2 month, respectively. In spite of widespread metastatic disease of M1c EGFR-m patients, their mOS (18.8 months) was longer than mOS of oligometastatic EGFR-wt patients (M1b), who had the lowest disease burden (14.4 months). Median follow up was 53.9 months. Conclusions Incorporation of EGFR mutation status in advanced NSCLC further differentiates survival curves of M categories in 8th TNM classification and more precisely predicts survival compared to number of metastasis or number of metastatic sites alone.

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

JMIR Cancer ◽  
10.2196/23161 ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e23161
Author(s):  
Michael Grabner ◽  
Cliff Molife ◽  
Liya Wang ◽  
Katherine B Winfree ◽  
Zhanglin Lin Cui ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Data Integration ◽  
Clinical Data ◽  
Real World ◽  
Administrative Claims ◽  
Data Set ◽  
Health Outcomes Research ◽  
Data Source ◽  
The Mean

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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