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Validation of algorithms to detect distant metastases in men with prostate cancer using routine registry data in Denmark

Authors Ehrenstein V, Hernandez RK, Maegbaek ML, Kahlert J, Nguyen-Nielsen M, Nørgaard M, Liede A

Received 26 September 2014

Accepted for publication 29 December 2014

Published 10 April 2015 Volume 2015:7 Pages 259—265

DOI https://doi.org/10.2147/CLEP.S74991

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Professor Henrik Toft Sørensen


Vera Ehrenstein,1 Rohini K Hernandez,2 Merete Lund Maegbaek,1 Johnny Kahlert,1 Mary Nguyen-Nielsen,1 Mette Nørgaard,1 Alexander Liede2

1Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 2Center for Observational Research, Amgen, Thousand Oaks, CA, USA

Objective: Among patients with prostate cancer, diagnostic codes for bone metastases in the Danish National Registry of Patients have a sensitivity of 44%. In an attempt to improve the sensitivity of registry-based identification of metastases from prostate cancer, we tested a series of algorithms, combining elevated prostate-specific antigen (PSA) levels, use of antiresorptive therapy, and performed bone scintigraphy.
Patients and methods: We randomly selected 212 men diagnosed with prostate cancer in 2005–2010 in the Central Denmark Region with prespecified PSA values, antiresorptive therapy, and bone scintigraphy who did not have a registry-based diagnostic code indicating presence of distant metastases. We defined three candidate algorithms for bone metastases: 1) PSA >50 µg/L and bone scintigraphy, 2) PSA >50 µg/L and antiresorptive therapy, and 3) PSA ≤50 µg/L with antiresorptive therapy or bone scintigraphy. An algorithm for distant metastasis site other than bone was defined as PSA >50 µg/L alone. Medical chart review was used as the reference standard to establish the presence or absence of metastases. Validity was expressed as a positive predictive value (PPV) or a negative predictive value, based on whether the algorithms correctly classified metastases compared with the reference standard.
Results: We identified 113 men with evidence of metastases according to the candidate algorithms, and 99 men without evidence of metastases according to the candidate algorithm. The PPVs of PSA >50 µg/L were 0.10 (95% confidence interval [CI] 0.04–0.19) for bone metastases and 0.14 (95% CI 0.07–0.24) for nonbone metastases, regardless of receipt of antiresorptive therapy or presence of bone scintigraphy. The PPVs for any metastases were 0.16 (95% CI 0.06–0.32) for PSA >50 µg/L and 0.28 (95% CI 0.14–0.47) for PSA >50 µg/L with bone scintigraphy. Adding antiresorptive treatment to the algorithm did not improve PPV. All negative predictive values approached 1.00.
Conclusion: Algorithms based on elevated PSA, antiresorptive therapy, or bone scintigraphy are not suitable for supplementing diagnostic codes to identify additional cases of distant metastases among men with prostate cancer. However, it is possible that in this setting, medical chart review is not a gold standard to identify metastases.

Keywords:
algorithm, bone metastases, prostate-specific antigen, validation, Danish databases

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