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Design of Retrospective and Case-Control Studies in Oncology

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Methods and Biostatistics in Oncology

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Abstract

Retrospective studies allow researchers to evaluate outcomes in a real-world setting at reduced costs compared with prospective trials, and have long-established use in surgical oncology. In retrospective studies, the study sample is generated from secondary or pre-existing data, which precludes randomization. As a result, the potential for unique and significant biases exists and these can limit the applicability and generalizability of the findings. This chapter is intended to serve as a guide for conducting retrospective research studies. Topics covered include internal and external validity; types of biases; sampling and matching techniques, including propensity score matching; missing data; and special considerations for common study designs. Examples from the surgical oncology literature are provided.

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Author information

Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Katherine S. Panageas Dr.P.H. & Debra A. Goldman M.S.

  2. Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    T. Peter Kingham M.D.

Authors
  1. Katherine S. Panageas Dr.P.H.
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  2. Debra A. Goldman M.S.
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  3. T. Peter Kingham M.D.
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Corresponding author

Correspondence to T. Peter Kingham M.D. .

Editor information

Editors and Affiliations

  1. Hospital do Câncer de Barretos, Barretos, São Paulo, Brazil

    Raphael. L.C Araújo

  2. AC Camargo Cancer Center, Dir - Brazil Gastrointestinal Tumor Grup, São Paulo, São Paulo, Brazil

    Rachel P. Riechelmann

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Panageas, K.S., Goldman, D.A., Kingham, T.P. (2018). Design of Retrospective and Case-Control Studies in Oncology. In: Araújo, R., Riechelmann, R. (eds) Methods and Biostatistics in Oncology. Springer, Cham. https://doi.org/10.1007/978-3-319-71324-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-71324-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71323-6

  • Online ISBN: 978-3-319-71324-3

  • eBook Packages: MedicineMedicine (R0)

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