Prognostic value of B-score for predicting joint replacement in the context of osteoarthritis phenotypes: Data from the osteoarthritis initiative.

Objective: Developing new therapies for knee osteoarthritis (KOA) requires improved prediction of disease progression. This study evaluated the prognostic value of clinical clusters and machine-learning derived quantitative 3D bone shape B-score for predicting total and partial knee replacement (KR). Design: This retrospective study used longitudinal data from the Osteoarthritis Initiative. A previous study used patients' clinical profiles to delineate phenotypic clusters. For these clusters, the distribution of B-scores was assessed (employing Tukey's method). The value of both cluster allocation and B-score for KR-prediction was then evaluated using multivariable Cox regression models and Kaplan-Meier curves for time-to-event analyses. The impact of using B-score vs. cluster was evaluated using a likelihood ratio test for the multivariable Cox model; global performances were assessed by concordance statistics (Harrell's C-index) and time dependent receiver operating characteristic (ROC) curves. Results: B-score differed significantly for the individual clinical clusters (p â€‹< â€‹0.001). Overall, 9.4% of participants had a KR over 9 years, with a shorter time to event in clusters with high B-score at baseline. Those clusters were characterized clinically by a high rate of comorbidities and potential signs of inflammation. Both phenotype and B-score independently predicted KR, with better prediction if combined (P â€‹< â€‹0.001). B-score added predictive value in groups with less pain and radiographic severity but limited physical activity. Conclusions: B-scores correlated with phenotypes based on clinical patient profiles. B-score and phenotype independently predicted KR surgery, with higher predictive value if combined. This can be used for patient stratification in drug development and potentially risk prediction in clinical practice.

Identifying oncogenic drivers associated with increased risk of late distant recurrence in postmenopausal, estrogen receptor-positive, HER2-negative early breast cancer: results from the BIG 1-98 study.

BACKGROUND: In postmenopausal, estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative early breast cancer, the risk for distant recurrence can extend beyond 5 years of adjuvant endocrine therapy. This study aims to identify genomic driver alterations associated with late distant recurrence. PATIENTS AND METHODS: Next generation sequencing was used to characterize driver alterations in primary tumors from a subset of 764 postmenopausal estrogen receptor-positive/HER2-negative patients from the BIG 1-98 randomized trial. Late distant recurrence events were defined as ≥5 years from time of randomization). The association of driver alterations with distant recurrence-free interval in early and late time periods was assessed using Cox regression models. Multivariable analyses were carried out to adjust for clinicopathological factors. Weighted analysis methods were used in order to correct for over-sampling of distant recurrences. RESULTS: A total of 538 of 764 (70%) samples were successfully sequenced including 88 (63%) early and 52 (37%) late distant recurrence events after a median follow up of 8.1 years. In univariable analysis for late distant recurrence, PIK3CA mutations (58.8%) were significantly associated with reduced risk [hazard ratio (HR) 0.40, 95% confidence interval (CI) 0.20-0.82, P = 0.012], whereas amplifications on chromosome 8p11 (10.9%) (HR 4.79, 95% CI 2.30-9.97, P < 0.001) and BRCA2 mutations (2.3%) (HR 5.39, 95% CI 1.51-19.29, P = 0.010) were significantly associated with an increased risk. In multivariable analysis, only amplifications on 8p11 (P = 0.002) and BRCA2 mutations (P = 0.013) remained significant predictors. CONCLUSIONS: In estrogen receptor-positive/HER2-negative postmenopausal early breast cancer, PIK3CA mutations were associated with reduced risk of late distant recurrence, whereas amplifications on 8p11 and BRCA2 mutations were associated with increased risk of late distant recurrence. The characterization of oncogenic driver alterations may aid in refining treatment choices in the late disease setting, and help identify potential drug targets for testing in future trials.

Are waterborne astrovirus implicated in acute digestive morbidity (E.MI.R.A. study)?

BACKGROUND: With rotavirus and Norwalk-like viruses, astroviruses are now recognized as important etiologic agents of viral gastroenteritis in all age groups. However, astrovirus is neither routinely screened for in stool samples, nor in environmental samples, and data on the health impact of waterborne astrovirus are lacking. OBJECTIVES: To assess the potential impact of astrovirus in drinking water on the incidence of acute digestive conditions (ADC) among a panel of volunteers. STUDY DESIGN: The Epidemiology and MIcrobial Risk Assessment (E.MI.R.A.) study combined a daily epidemiological follow-up of digestive morbidity among a panel of 544 volunteers supplied by French public water systems, and a microbiological surveillance of drinking water. Cases of digestive morbidity were collected through weekly telephone calls. The bacterial, virological and parasitic quality of tap water was assessed monthly. Additional samples were collected if the incidence of ADC increased. The relationship between incidence of ADC during a 7-day period centered about the water sampling day and astrovirus RNA prevalence in drinking water was modeled by regression techniques, taking into account several confounders. RESULTS: 12% (8/68) of the analyzed water samples were positive for astrovirus, and presence of astrovirus RNA was associated with a significant increased risk of ADC: RR=1.51 (95% CI=[1.17-1.94], P value=0.002). CONCLUSIONS: This result suggests a role for waterborne astrovirus in the endemic level of digestive morbidity in the general population. Perhaps astrovirus is a candidate test target for viral surveillance of drinking water.