Int. Journal of Clinical Pharmacology and Therapeutics, Volume 64 (2026) - August (391 - 397)

Development of a pain intensity estimation model in breast cancer survivors using quantile regression: A nationwide claims-based cohort study

Jin Lee1, 2, Alexsandre Chan3, Juhee Cho1, 2, 4, 5*, Hwa Jeong Seo6, 7*
1 Department of Clinical Research Design and Evaluation, SAIHST, 2 Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University, Seoul, South Korea, 3 Department of Clinical Pharmacy Practice, School of Pharmacy & Pharmaceutical Sciences, University of California, Irvine, CA, USA, 4 Cancer Education Center, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, 5 Department of Digital Health, Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, 6 Medical Informatics and Health Technology (MiT), Department of Healthcare Industry Management, and 7 Global Healthcare Research Institute, Gachon University, Seongnam, South Korea

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DOI 10.5414/CP204804

Abstract

Objective: In patients in whom pain cannot be objectively evaluated, achieving high compliance with symptom management is challenging. This study aimed to estimate pain-related factors and pain intensity in patients with breast cancer according to prescription history of analgesics.
Materials and methods: Pain intensity was rated according to low, moderate, and high cumulative analgesic consumption score (CACS). CACS-based quantile regression analysis was performed considering sociodemographic (age, income, and disease duration), index-related (body mass index (BMI) and Charlson Comorbidity Index (CCI)), and surgery- and treatment-related variables.
Results: In the mild pain group (Q1), age (≥ 50 years; βQ1 = 0.5803) and BMI (≥ 25; βQ1 = 0.7062) -affected the pain estimate. In the moderate-pain group (Q2), age (≥ 50 years; βQ2 = 1.0380), BMI (≥ 25; βQ2 = 0.9011), CCI (≥ 3; β<sub>Q2</sub> = 0.6106) and radiation therapy (yes; βQ2 = 0.5652) affected pain intensity. In the severe-pain group (Q4), age (≥ 50 years; βQ4 = 7.002), BMI (≥ 25; βQ4 = 6.2800), CCI (≥ 3; βQ4 = 3.4480), lymph node dissection (yes; βQ4 = 2.4420), and lymphedema (yes; βQ4 = 4.6580) affected pain estimate.
Conclusion: Among patients with breast cancer, older age, longer disease duration, higher BMI and CCI, prior lymph node dissection, and lymphedema presence may contribute to more severe pain symptoms. These findings may pave the way for the development of preemptive pain intervention for patients with breast cancer.

Author Details

Authors

Departments

  • 1 Department of Clinical Research Design and Evaluation, SAIHST,
  • 2 Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University, Seoul, South Korea,
  • 3 Department of Clinical Pharmacy Practice, School of Pharmacy &amp; Pharmaceutical Sciences, University of California, Irvine, CA, USA,
  • 4 Cancer Education Center, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine,
  • 5 Department of Digital Health, Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul,
  • 6 Medical Informatics and Health Technology (MiT), Department of Healthcare Industry Management, and
  • 7 Global Healthcare Research Institute, Gachon University, Seongnam, South Korea

Address

Juhee Cho or Hwa Jeong Seo
Medical informatics and health Technology (MiT)
Department of Healthcare Industry Management
Gachon University
1342 Seongnamdaero, Sujeong-gu,
Seongnam 13120, Gyeinggi-do, South Korea
Email: [email protected]; [email protected]

Citation

Jin Lee, Alexsandre Chan, Juhee Cho, Hwa Jeong Seo.Development of a pain intensity estimation model in breast cancer survivors using quantile regression: A nationwide claims-based cohort study
. Int J Clin Pharmacol Ther. 2026; 64: 391-397. doi: 10.5414/CP204804. Pubmed: https://pubmed.ncbi.nlm.nih.gov/42163631/; PMID: 42163631.

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