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

Jin Lee, Alexsandre Chan, Juhee Cho, and Hwa Jeong Seo

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Volume 64 (2026) p. 391 - 397

Abstract

International Journal of Clinical Pharmacology and Therapeutics, Vol. 64 – No. 8/2026 (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*, and Hwa Jeong Seo⁶#⁷*

¹Department of Clinical Research Design and Evaluation, SAIHST, ²Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University, Seoul, South Korea, ³Department of Clinical Pharmacy Practice, School of Pharmacy & Pharmaceutical Sciences, University of California, Irvine, CA, USA, ⁴Cancer Education Center, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, ⁵Department of Digital Health, Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, ⁶Medical Informatics and Health Technology (MiT), Department of Healthcare Industry Management, and ⁷Global Healthcare Research Institute, Gachon University, Seongnam, South Korea
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; β_Q1 = 0.5803) and BMI (≥ 25; β_Q1 = 0.7062) -affected the pain estimate. In the moderate-pain group (Q2), age (≥ 50 years; β_Q2 = 1.0380), BMI (≥ 25; β_Q2 = 0.9011), CCI (≥ 3; β<sub>Q2</sub> = 0.6106) and radiation therapy (yes; β_Q2 = 0.5652) affected pain intensity. In the severe-pain group (Q4), age (≥ 50 years; β_Q4 = 7.002), BMI (≥ 25; β_Q4 = 6.2800), CCI (≥ 3; β_Q4 = 3.4480), lymph node dissection (yes; β_Q4 = 2.4420), and lymphedema (yes; β_Q4 = 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.Correspondence to:
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]

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