Literature DB >> 23796301

A checklist for ascertaining study cohorts in oncology health services research using secondary data: report of the ISPOR oncology good outcomes research practices working group.

Kathy L Schulman1, Karina Berenson, Ya-Chen Tina Shih, Kathleen A Foley, Arijit Ganguli, Jonas de Souza, Nicholas A Yaghmour, Alex Shteynshlyuger.   

Abstract

OBJECTIVES: The ISPOR Oncology Special Interest Group formed a working group at the end of 2010 to develop standards for conducting oncology health services research using secondary data. The first mission of the group was to develop a checklist focused on issues specific to selection of a sample of oncology patients using a secondary data source.
METHODS: A systematic review of the published literature from 2006 to 2010 was conducted to characterize the use of secondary data sources in oncology and inform the leadership of the working group prior to the construction of the checklist. A draft checklist was subsequently presented to the ISPOR membership in 2011 with subsequent feedback from the larger Oncology Special Interest Group also incorporated into the final checklist.
RESULTS: The checklist includes six elements: identification of the cancer to be studied, selection of an appropriate data source, evaluation of the applicability of published algorithms, development of custom algorithms (if needed), validation of the custom algorithm, and reporting and discussions of the ascertainment criteria. The checklist was intended to be applicable to various types of secondary data sources, including cancer registries, claims databases, electronic medical records, and others.
CONCLUSIONS: This checklist makes two important contributions to oncology health services research. First, it can assist decision makers and reviewers in evaluating the quality of studies using secondary data. Second, it highlights methodological issues to be considered when researchers are constructing a study cohort from a secondary data source.
Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23796301     DOI: 10.1016/j.jval.2013.02.006

Source DB:  PubMed          Journal:  Value Health        ISSN: 1098-3015            Impact factor:   5.725


  10 in total

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2.  Validation of an International Classification of Disease, 10th revision coding adaptation for the Charlson Comorbidity Index in United States healthcare claims data.

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3.  Development and Validation of an Algorithm to Identify Patients with Multiple Myeloma Using Administrative Claims Data.

Authors:  Nicole Princic; Chris Gregory; Tina Willson; Maya Mahue; Diana Felici; Winifred Werther; Gregory Lenhart; Kathleen A Foley
Journal:  Front Oncol       Date:  2016-10-27       Impact factor: 6.244

4.  Identifying multiple myeloma patients using data from the French health insurance databases: Validation using a cancer registry.

Authors:  Aurore Palmaro; Martin Gauthier; Cécile Conte; Pascale Grosclaude; Fabien Despas; Maryse Lapeyre-Mestre
Journal:  Medicine (Baltimore)       Date:  2017-03       Impact factor: 1.889

5.  Incidence of advanced colorectal cancer in Germany: comparing claims data and cancer registry data.

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Journal:  BMC Med Res Methodol       Date:  2019-07-08       Impact factor: 4.615

6.  Clinical and economic burden of head and neck cancer: a nationwide retrospective cohort study from France.

Authors:  Antoine Schernberg; Luis Sagaon-Teyssier; Michaël Schwarzinger
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7.  Validity of breast, lung and colorectal cancer diagnoses in administrative databases: a systematic review protocol.

Authors:  Iosief Abraha; Gianni Giovannini; Diego Serraino; Mario Fusco; Alessandro Montedori
Journal:  BMJ Open       Date:  2016-03-18       Impact factor: 2.692

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

Authors:  Ralph M Turner; Yen-Wen Chen; Ancilla W Fernandes
Journal:  Front Pharmacol       Date:  2017-11-30       Impact factor: 5.810

9.  Accuracy of administrative databases in detecting primary breast cancer diagnoses: a systematic review.

Authors:  Iosief Abraha; Alessandro Montedori; Diego Serraino; Massimiliano Orso; Gianni Giovannini; Valeria Scotti; Annalisa Granata; Francesco Cozzolino; Mario Fusco; Ettore Bidoli
Journal:  BMJ Open       Date:  2018-07-23       Impact factor: 2.692

10.  Evaluation of the accuracy of algorithms to identify soft tissue sarcoma (STS) in administrative claims.

Authors:  Nicole Princic; Donna McMorrow; Philip Chan; Lisa Hess
Journal:  Clin Sarcoma Res       Date:  2020-05-05
  10 in total

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