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

Author

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  • Andrea Spini

    (INSERM, BPH, U1219, Team Pharmacoepidemiology, University of Bordeaux, 33000 Bordeaux, France
    Department of Medical Science, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy)

  • Giulia Hyeraci

    (Osservatorio di Epidemiologia, Agenzia Regionale di Sanità Della Toscana, 50141 Florence, Italy)

  • Claudia Bartolini

    (Osservatorio di Epidemiologia, Agenzia Regionale di Sanità Della Toscana, 50141 Florence, Italy)

  • Sandra Donnini

    (Department of Life Sciences, University of Siena, 53100 Siena, Italy)

  • Pietro Rosellini

    (CIC1401, CIC Bordeaux, 33000 Bordeaux, France
    Pole de Santé Publique, Service de Pharmacologie Médicale, Centre de Pharmacovigilance de Bordeaux, CHU de Bordueax, 33000 Bordeaux, France)

  • Rosa Gini

    (Osservatorio di Epidemiologia, Agenzia Regionale di Sanità Della Toscana, 50141 Florence, Italy)

  • Marina Ziche

    (Department of Medical Science, Surgery and Neuroscience, University of Siena, 53100 Siena, Italy)

  • Francesco Salvo

    (INSERM, BPH, U1219, Team Pharmacoepidemiology, University of Bordeaux, 33000 Bordeaux, France
    Pole de Santé Publique, Service de Pharmacologie Médicale, Centre de Pharmacovigilance de Bordeaux, CHU de Bordueax, 33000 Bordeaux, France)

  • Giuseppe Roberto

    (Osservatorio di Epidemiologia, Agenzia Regionale di Sanità Della Toscana, 50141 Florence, Italy)

Abstract

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.

Suggested Citation

  • Andrea Spini & Giulia Hyeraci & Claudia Bartolini & Sandra Donnini & Pietro Rosellini & Rosa Gini & Marina Ziche & Francesco Salvo & Giuseppe Roberto, 2021. "Real-World Utilization of Target- and Immunotherapies for Lung Cancer: A Scoping Review of Studies Based on Routinely Collected Electronic Healthcare Data," IJERPH, MDPI, vol. 18(14), pages 1-21, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7679-:d:597307
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    References listed on IDEAS

    as
    1. Kurt Benke & Geza Benke, 2018. "Artificial Intelligence and Big Data in Public Health," IJERPH, MDPI, vol. 15(12), pages 1-9, December.
    2. Corinne Willame & Caitlin Dodd & Lieke van der Aa & Gino Picelli & Hanne-Dorthe Emborg & Johnny Kahlert & Rosa Gini & Consuelo Huerta & Elisa Martín-Merino & Chris McGee & Simon Lusignan & Giuseppe Ro, 2021. "Incidence Rates of Autoimmune Diseases in European Healthcare Databases: A Contribution of the ADVANCE Project," Drug Safety, Springer, vol. 44(3), pages 383-395, March.
    3. Giuseppe Roberto & Ingrid Leal & Naveed Sattar & A Katrina Loomis & Paul Avillach & Peter Egger & Rients van Wijngaarden & David Ansell & Sulev Reisberg & Mari-Liis Tammesoo & Helene Alavere & Alessan, 2016. "Identifying Cases of Type 2 Diabetes in Heterogeneous Data Sources: Strategy from the EMIF Project," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-18, August.
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