1. Clinical Predictors for Analgesic Response to Radiotherapy in Patients with Painful Bone Metastases
- Author
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Pål Klepstad, Ragnhild Habberstad, Jason W Boland, Cinzia Brunelli, Nina Aass, Romina Rossi, Tatiana Mikhailovna Abramova, Ellen Bjerkeset, Jo-Åsmund Lund, Trude Camilla Salvesen Frøseth, Mariangela Caputo, Elena Garcia-Alonso, and Stein Kaasa
- Subjects
Adult ,Male ,medicine.medical_specialty ,Palliative care ,medicine.medical_treatment ,Analgesic ,Pain ,Bone Neoplasms ,03 medical and health sciences ,Prostate cancer ,0302 clinical medicine ,Breast cancer ,Internal medicine ,medicine ,Clinical endpoint ,Humans ,030212 general & internal medicine ,Bone pain ,General Nursing ,Pain Measurement ,Analgesics ,biology ,Performance status ,business.industry ,C-reactive protein ,Palliative Care ,Cancer ,Bone metastasis ,Hematology ,Odds ratio ,medicine.disease ,Confidence interval ,Radiation therapy ,Anesthesiology and Pain Medicine ,Oncology ,030220 oncology & carcinogenesis ,biology.protein ,Neurology (clinical) ,medicine.symptom ,business - Abstract
Background Radiationtherapy (RT) provide pain reduction in about 60% of patients with painful bone metastases. Studies have identified demographic and clinical characteristics to predict RT response, but no model is clinical useful. Tumor characteristics and inflammation can influence cancer induced bone pain, but the association with RT response are not studied. We test if tumor characteristics and the inflammation marker CRP improve prediction of RT response. Methods We included adult patients receiving RT for painful bone metastases in a multicenter, multinational longitudinal observational study. The primary endpoint was analgesic response within 8 weeks after RT defined according to current guidelines. Seventeen independent potential predictor variables assessed at baseline included patient demographics, RT administration, pain characteristics and treatment, cancer diagnosis, tumor characteristics, depression and inflammation (CRP). Multivariate logistic regression analysis with multiple imputation of missing data were applied to identify predictors of RT response. Results are reported as odds ratios (OR) and 95% confidence intervals (CI). Results 565 eligible patients were enrolled, 424 patients (75%) had complete data on the variables of interest and multiple imputation allowed the final regression models to be carried out on 513 patients (91%). 232 patients (41%, CI 37%-45%) responded to RT. Higher Karnofsky performance status (OR 1.45, CI 1.21-1.73), breast cancer (OR 2.61, CI 1.20-5.69) and prostate cancer (OR 2.64, CI 1.24-5.63) (compared to GI cancer), presence of soft tissue expansion (OR 1.78, CI 1.13-2.81) and higher maximum pain intensity at the radiated site (OR 1.1, CI 1.00-1.21) were significant predictors of positive RT response, while the use of steroids was a negative predictor (OR 0.62, CI 0.42-0.93). The discriminative ability of the model was moderate, with C-statistics 0.70. Conclusions This study supports previous findings that higher performance status, cancer diagnosis and higher baseline pain intensity predict analgesic RT response. The study presents new data showing that presence of soft tissue expansion predicts RT response and that CRP is not significantly associated with analgesic RT response. Clinical trial identification NCT02107664 (Date of registration April 8, 2014). Legal entity responsible for the study Pal Klepstad. Funding The European Palliative Care Research Centre (PRC). Disclosure All authors have declared no conflicts of interest.
- Published
- 2021