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Prognostic models for predicting overall survival in metastatic castration-resistant prostate cancer: a systematic review

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Abstract

Purpose

Prognostic models are developed to estimate the probability of the occurrence of future outcomes incorporating multiple variables. We aimed to identify and summarize existing multivariable prognostic models developed for predicting overall survival in patients with metastatic castration-resistant prostate cancer (mCRPC).

Methods

The protocol was prospectively registered (CRD42017064448). We systematically searched Medline and reference lists up to May 2018 and included experimental and observational studies, which developed and/or internally validated prognostic models for mCRPC patients and were further externally validated or updated. The outcome of interest was overall survival. Two authors independently performed literature screening and quality assessment.

Results

We included 12 studies that developed models including 8750 patients aged 42–95 years. Models included 4–11 predictor variables, mostly hemoglobin, baseline PSA, alkaline phosphatase, performance status, and lactate dehydrogenase. Very few incorporated Gleason score. Two models included predictors related to docetaxel and mitoxantrone treatments. Model performance after internal validation showed similar discrimination power ranging from 0.62 to 0.73. Overall survival models were mainly constructed as nomograms or risk groups/score. Two models obtained an overall judgment of low risk of bias.

Conclusions

Most models were not suitable for clinical use due to methodological shortcomings and lack of external validation. Further external validation and/or model updating is required to increase prognostic accuracy and clinical applicability prior to their incorporation in clinical practice as a useful tool in patient management.

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Abbreviations

ADT:

Androgen deprivation therapy

ARSi:

Androgen receptor signaling inhibitors

c-index:

Concordance index

CHARMS:

Checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies

CRP:

C-reactive protein

CRPC:

Castration-resistant prostate cancer

DREAM:

Dialogue for reverse engineering assessments and methods

ECOG:

Eastern Cooperative Oncology Group

GnRH:

Gonadotrophin-releasing hormone

LDH:

Lactate dehydrogenase

mCRPC:

Metastatic castration-resistant prostate cancer

PCa:

Prostate cancer

PSA:

Prostate-specific antigen

PRISMA:

Preferred reporting items for systematic reviews and meta-analyses statement

PROBAST:

Prediction model study risk of bias assessment tool

RCTs:

Randomized clinical trials

REMARK:

Reporting recommendations for tumor marker prognostic studies

tAUC:

Time-dependent area under the curve

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Acknowledgements

We would like to thank Dr. Robert Wolff for his comments and suggestions to the manuscript. B. Wullich, University Hospital Erlangen, Erlangen, Germany. C. Becker, Deutsche Gesellschaft für Urologie, Düsseldorf, Germany. G. Kristiansen, University Hospital Bonn, Bonn, Germany. G. Seitz, Hospital Bamberg, Bamberg, Germany. J. Linxweiler, University Hospital Saarland, Homburg, Germany. S. Füssel, University Hospital Dresden, Dresden, Germany. S. Wach, University Hospital Erlangen, Erlangen, Germany.

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  1. M. Pinart and F. Kunath have contributed equally to this work.

Authors and Affiliations

  1. Department of Urology and Pediatric Urology, University Hospital Erlangen, Erlangen, Germany

    M. Pinart, F. Kunath, V. Lieb & B. Wullich

  2. UroEvidence@Deutsche Gesellschaft für Urologie, Berlin, Germany

    M. Pinart, F. Kunath & Stefanie Schmidt

  3. Department of Urology, University Medicine Mainz, Mainz, Germany

    I. Tsaur

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  1. M. Pinart
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German Prostate Cancer Consortium (DPKK)

  • B. Wullich
  • , C. Becker
  • , G. Kristiansen
  • , G. Seitz
  • , J. Linxweiler
  • , S. Füssel
  •  & S. Wach

Contributions

M. Pinart: protocol development, data collection and management, data analysis, manuscript writing and editing. F. Kunath: protocol development, manuscript writing and editing. V. Lieb: manuscript writing and editing. I. Tsaur: manuscript writing and editing. B. Wullich: manuscript writing and editing. S. Schmidt: project development, protocol development, data collection and management, data analysis, manuscript writing and editing.

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Correspondence to Stefanie Schmidt.

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Pinart, M., Kunath, F., Lieb, V. et al. Prognostic models for predicting overall survival in metastatic castration-resistant prostate cancer: a systematic review. World J Urol 38, 613–635 (2020). https://doi.org/10.1007/s00345-018-2574-2

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