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Updated: Feb 27, 2026
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Published on: April 12, 2021
Construction, internal validation and implementation in a mobile application of a scoring system to predict
Emma Mares-García1, Antonio Palazón-Bru1, David Manuel Folgado-de la Rosa1
1Department of Clinical Medicine, Miguel Hernández University, San Juan de Alicante, Alicante, Spain.
Background:
Other studies have assessed nonadherence to proton pump inhibitors (PPIs), but none has developed a screening test for its detection.
Objectives:
To construct and internally validate a predictive model for nonadherence to PPIs.
Methods:
This prospective observational study with a one-month follow-up was carried out in 2013 in Spain, and included 302 patients with a prescription for PPIs. The primary variable was nonadherence to PPIs (pill count). Secondary variables were gender, age, antidepressants, type of PPI, non-guideline-recommended prescription (NGRP) of PPIs, and total number of drugs. With the secondary variables, a binary logistic regression model to predict nonadherence was constructed and adapted to a points system. The ROC curve, with its area (AUC), was calculated and the optimal cut-off point was established. The points system was internally validated through 1,000 bootstrap samples and implemented in a mobile application (Android).
Results:
The points system had three prognostic variables: total number of drugs, NGRP of PPIs, and antidepressants. The AUC was 0.87 (95% CI [0.83-0.91], p < 0.001). The test yielded a sensitivity of 0.80 (95% CI [0.70-0.87]) and a specificity of 0.82 (95% CI [0.76-0.87]). The three parameters were very similar in the bootstrap validation.
Conclusions:
A points system to predict nonadherence to PPIs has been constructed, internally validated and implemented in a mobile application. Provided similar results are obtained in external validation studies, we will have a screening tool to detect nonadherence to PPIs.
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