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  1. Home
  2. Investigating The Risk Factors For Nonadherence To Analgesic Medications In Cancer Patients: Establishing A Nomogram Model.
  1. Home
  2. Investigating The Risk Factors For Nonadherence To Analgesic Medications In Cancer Patients: Establishing A Nomogram Model.

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Investigating the risk factors for nonadherence to analgesic medications in cancer patients: Establishing a nomogram

Ying Wang1, ChanChan Hu2, Junhui Hu1

  • 1Department of Pharmacy, The Affiliated Hospital of Chengde Medical University, Chengde, Hebei, 067000, PR China.

Heliyon
|April 1, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

A new nomogram model accurately predicts analgesic medication nonadherence in cancer patients. This tool aids long-term pain management by identifying patients at risk, improving adherence and healthcare efficiency.

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Area of Science:

  • Oncology
  • Pharmacology
  • Biostatistics

Background:

  • Nonadherence to analgesic medication is prevalent in cancer patients, straining healthcare systems.
  • Effective management of cancer pain requires understanding and addressing medication nonadherence.

Purpose of the Study:

  • To develop and validate a nomogram model for assessing analgesic medication nonadherence in cancer patients.
  • To identify key risk factors contributing to nonadherence in this population.

Main Methods:

  • A retrospective study analyzed clinical, demographic, and adherence data from 450 cancer pain patients.
  • Risk factors were identified using LASSO and multivariate logistic regression.
  • A nomogram was developed and validated using bootstrap methods, C-index, ROC curves, and calibration plots.

Main Results:

  • The study identified seven significant risk factors for nonadherence: age, address, smoking history, comorbidities, NSAID use, opioid use, and PHQ-8 score.
  • The developed nomogram demonstrated strong predictive performance with a C-index of 0.93 and an AUC of 0.929.
  • Decision curve analysis confirmed the model's clinical utility in predicting medication adherence.

Conclusions:

  • A validated nomogram model incorporating seven risk factors has been developed for cancer patients.
  • This tool supports long-term analgesic management by predicting nonadherence.
  • The model offers a valuable approach to improving medication adherence in cancer pain management.