Real-World Utilization of Target- and Immunotherapies for Lung Cancer: A Scoping Review of Studies Based on Routinely Collected Electronic Healthcare Data.
Andrea SpiniGiulia HyeraciClaudia BartoliniSandra DonniniPietro RoselliniRosa GiniMarina ZicheFrancesco SalvoGiuseppe RobertoPublished in: International journal of environmental research and public health (2021)
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.
Keyphrases
- healthcare
- case control
- electronic health record
- big data
- end stage renal disease
- systematic review
- newly diagnosed
- squamous cell carcinoma
- ejection fraction
- data analysis
- peritoneal dialysis
- machine learning
- randomized controlled trial
- patient reported outcomes
- deep learning
- high resolution
- high resolution mass spectrometry
- bone marrow
- drug induced
- tandem mass spectrometry
- lymph node metastasis
- squamous cell
- cell therapy
- health promotion