How Do Pain Characteristics, Comorbidity Severity and Patient Characteristics Influence Chronic Pain Patients’ Self-Management Priorities?

Introduction/Aim: More than half of chronic pain patients suffer from other chronic health conditions. This study aims to 1) examine the degree to which pain management is a priority among individuals with multiple medical conditions and 2) identify predictors of pain prioritization. Methods: The sample is comprised of 99 patients suffering from chronic pain (≥ 3 months) and ≥ 1 other medical condition recruited through patient associations and social/conventional media. Self-report questionnaires (pain characteristics, patient characteristics, type and severity of comorbidities) were completed at baseline and a pain prioritization diary was completed twice weekly for 6 weeks. Univariate regression models were used to identify pain, patient and comorbidity variables (p > 0.20) that would be included in a final multivariate model to examine pain management priority (model 1) and stability of prioritization (model 2). Results: Pain management prioritization scores ranged from 1.67 to 4.92 out of 5 (SD = 0.76) and 16.2% of participants reported ≥ 20% increase or decrease in the priority given to pain management over a six-week period. Model 1: Perceived illness burden was the only predictor retained in the univariate analysis (p = 0.074) to predict levels of pain management prioritization. Model 2: None of the characteristics examined were significantly associated with stability of prioritization of pain management symptoms. Discussion/Conclusions: Prioritization of pain management is a dynamic process that does not seem to be influenced by severity of pain, individual characteristics or severity of comorbidities. The next step is to examine time-varying predictors of pain management prioritization

Association and performance of polygenic risk scores for breast cancer among French women presenting or not a familial predisposition to the disease

International audienceBackground: Three partially overlapping breast cancer polygenic risk scores (PRS) comprising 77, 179 and 313 SNPs have been proposed for European-ancestry women by the Breast Cancer Association Consortium (BCAC) for improving risk prediction in the general population. However, the effect of these SNPs may vary from one country to another and within a country because of other factors. Objective: To assess their associated risk and predictive performance in French women from (1) the CECILE population-based case-control study, (2) BRCA1 or BRCA2 (BRCA1/2) pathogenic variant (PV) carriers from the GEMO study, and (3) familial breast cancer cases with no BRCA1/2 PV and unrelated controls from the GENESIS study. Results: All three PRS were associated with breast cancer in all studies, with odds ratios per standard deviation varying from 1.7 to 2.0 in CECILE and GENESIS, and hazard ratios varying from 1.1 to 1.4 in GEMO. The predictive performance of PRS313 in CECILE was similar to that reported in BCAC but lower than that in GENESIS (area under the receiver operating characteristic curve (AUC) = 0.67 and 0.75, respectively). PRS were less performant in BRCA2 and BRCA1 PV carriers (AUC = 0.58 and 0.54 respectively). Conclusion: Our results are in line with previous validation studies in the general population and in BRCA1/2 PV carriers. Additionally, we showed that PRS may be of clinical utility for women with a strong family history of breast cancer and no BRCA1/2 PV, and for those carrying a predicted PV in a moderate-risk gene like ATM, CHEK2 or PALB2