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. 2024 Feb 3;24(1):28.
doi: 10.1186/s12894-024-01421-y.

Converting between the International Prostate Symptom Score (IPSS) and the Expanded Prostate Cancer Index Composite (EPIC) urinary subscales: modeling and external validation

Paul Windisch  1 , Ivo Becker  2 , Hongjian Tang  3 , Christina Schröder  3 , André Buchali  4 , Daniel M Aebersold  2 , Daniel R Zwahlen  3 , Robert Förster #  3 , Mohamed Shelan #  2
Affiliations

Converting between the International Prostate Symptom Score (IPSS) and the Expanded Prostate Cancer Index Composite (EPIC) urinary subscales: modeling and external validation

Paul Windisch et al. BMC Urol. .

Abstract

Background: Prostate-related quality of life can be assessed with a variety of different questionnaires. The 50-item Expanded Prostate Cancer Index Composite (EPIC) and the International Prostate Symptom Score (IPSS) are two widely used options. The goal of this study was, therefore, to develop and validate a model that is able to convert between the EPIC and the IPSS to enable comparisons across different studies.

Methods: Three hundred forty-seven consecutive patients who had previously received radiotherapy and surgery for prostate cancer at two institutions in Switzerland and Germany were contacted via mail and instructed to complete both questionnaires. The Swiss cohort was used to train and internally validate different machine learning models using fourfold cross-validation. The German cohort was used for external validation.

Results: Converting between the EPIC Urinary Irritative/Obstructive subscale and the IPSS using linear regressions resulted in mean absolute errors (MAEs) of 3.88 and 6.12, which is below the respective previously published minimal important differences (MIDs) of 5.2 and 10 points. Converting between the EPIC Urinary Summary and the IPSS was less accurate with MAEs of 5.13 and 10.45, similar to the MIDs. More complex model architectures did not result in improved performance in this study. The study was limited to the German versions of the respective questionnaires.

Conclusions: Linear regressions can be used to convert between the IPSS and the EPIC Urinary subscales. While the equations obtained in this study can be used to compare results across clinical trials, they should not be used to inform clinical decision-making in individual patients.

Trial registration: This study was retrospectively registered on clinicaltrials.gov on January 14th, 2022, under the registration number NCT05192876.

Keywords: EPIC; IPSS; Prostate; Quality of life.

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Conflict of interest statement

P.W. has a patent application titled ‘Method for detection of neurological abnormalities’ outside of the submitted work. The remaining authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Visualization of selected patient characteristics. Translucent bands in the scatterplots indicate the 95% confidence interval of the regression. PCC = Pearson Correlation Coefficient
Fig. 2
Fig. 2
Results of the baseline linear regression models on the external validation set. The coordinates of the dots are determined by the value the model predicted for a given patient in a given questionnaire vs. the actual value the patient obtained. Please note that for the IPSS, lower MAEs are expected due to the scale only ranging from 0–35 compared to the EPIC, which ranges from 0–100. MAE = Mean Absolute Error
Fig. 3
Fig. 3
Results of different model architectures for predicting the EPIC Urinary Summary (top) or Urinary Irritative/Obstructive (bottom) subscales on the external validation set using all IPSS questions. MAE = Mean Absolute Error
Fig. 4
Fig. 4
Results of different model architectures for predicting the total IPSS using all EPIC Urinary subscale questions (top) or only the most relevant EPIC Urinary subscale questions (bottom). MAE = Mean Absolute Error
See this image and copyright information in PMC

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