JoVE - Journal of Visualized Experiments
JoVE Visualize
Contact Us

Classification of Patients With Painful Tumors to Predict Response to Palliative Radiation Therapy

  • 0Department of Radiation Oncology, Aichi Cancer Center Hospital, Chikusa-ku, Nagoya, Japan.
International Journal of Radiation Oncology, Biology, Physics +

|

March 17, 2024

|

March 17, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Opioid use and reirradiation significantly impact pain relief from palliative radiation therapy (RT). Patients receiving RT without these factors showed better pain response rates and slower progression.

Area Of Science

  • Oncology
  • Palliative Care
  • Radiation Oncology

Background

  • Palliative radiation therapy (RT) is crucial for managing cancer pain.
  • Identifying factors influencing pain response is essential for optimizing treatment outcomes.
  • Patient classification systems can personalize palliative RT strategies.

Purpose Of The Study

  • To identify factors affecting pain response in patients undergoing palliative RT.
  • To develop a patient classification system for palliative RT based on these factors.

Main Methods

  • Prospective observational study of 261 patients receiving palliative RT for painful tumors.
  • Pain response assessed using International Consensus Pain Response Endpoints criteria.
  • Multivariable logistic regression used to identify predictive factors and develop a classification system.

Main Results

  • A 60% overall pain response rate was observed within 12 weeks, with average pain scores decreasing from 6.1 to 3.4.
  • Opioid use and reirradiation were identified as negative predictors of pain response (P < .01).
  • A three-class system (no opioid/reirradiation, intermediate, opioid/reirradiation) showed response rates of 75%, 61%, and 36%, respectively (P < .001), with significant differences in progression rates.

Conclusions

  • Opioid use and reirradiation significantly influence pain response rates and progression in palliative RT.
  • A patient classification system incorporating these factors can predict treatment outcomes.
  • Personalized palliative RT approaches are warranted based on patient-specific factors.