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A high percentage of patients referred for unexplained pain after TKA had early-grade osteoarthritis preoperatively. Patients undergoing TKA for less than Grade 3 or 4 OA should be informed that they may be at higher risk for persistent pain and dissatisfaction.

Objective Homologous recombination (HR) proficient ovarian cancers, including CCNE1 (cyclin E)-amplified tumors, are resistant to poly (ADP-ribose) polymerase inhibitors (PARPi). Histone deacetylase inhibitors (HDACi) are effective in overcoming tumor resistance to DNA damaging drugs. Our goal was to determine whether panobinostat, a newly FDA-approved HDACi, can sensitize cyclin E, HR-proficient ovarian cancer cells to the PARPi olaparib. Methods Expression levels of CCNE1 (cyclin E), BRCA1, RAD51 and E2F1 in ovarian tumors and cell lines were extracted from The Cancer Genome Atlas (TCGA) and Broad-Novartis Cancer Cell Line Encyclopedia (CCLE). In HR-proficient ovarian cancer cell line models (OVCAR-3, OVCAR-4, SKOV-3, and UWB1.289 + BRCA1 wild-type), cell growth and viability were assessed by sulforhodamine B and xenograft assays. DNA damage and repair (pH2AX and RAD51 co-localization and DRGFP reporter activity) and apoptosis (cleaved PARP and cleaved caspase-3) were assessed by immunofluorescence and Western blot assays. Results TCGA and CCLE data revealed positive correlations (Spearman) between cyclin E E2F1, and E2F1 gene targets related to DNA repair (BRCA1 and RAD51). Panobinostat downregulated cyclin E and HR repair pathway genes, and reduced HR efficiency in cyclin E-amplified OVCAR-3 cells. Further, panobinostat synergized with olaparib in reducing cell growth and viability in HR-proficient cells. Similar co-operative effects were observed in xenografts, and on pharmacodynamic markers of HR repair, DNA damage and apoptosis. Conclusions These results provide preclinical rationale for using HDACi to reduce HR in cyclin E-overexpressing and other types of HR-proficient ovarian cancer as a means of enhancing PARPi activity.

Background: Implant malalignment may predispose patients to prosthetic failure following total knee arthroplasty (TKA). A more thorough understanding of the surgeon-specific factors that contribute to implant malalignment following TKA may uncover actionable strategies for improving implant survival. The purpose of this study was to determine the impact of surgeon volume and training status on malalignment. Methods: In this retrospective multicenter study, we performed a radiographic analysis of 1,570 primary TKAs performed at 4 private academic and state-funded centers in the U.S. and U.K. Surgeons were categorized as high-volume (‡50 TKAs/ year) or low-volume (<50 TKAs/year), and as a trainee (fellow/resident under the supervision of an attending surgeon) or a non-trainee (attending surgeon). On the basis of these designations, 3 groups were defined: high-volume non-trainee, lowvolume non-trainee, and trainee. The postoperative medial distal femoral angle (DFA), medial proximal tibial angle (PTA), and posterior tibial slope angle (PSA) were radiographically measured. Outlier measurements were defined as follows: DFA, outside of 5°± 3°of valgus; PTA, >±3°deviation from the neutral axis; and PSA, <0°or >7°of flexion for cruciate-retaining or <0°or >5°of flexion for posterior-stabilized TKAs. "Far outliers" were defined as measurements falling >± 2°outside of these ranges. The proportions of outliers were compared between the groups using univariate and multivariate analyses. Results: When comparing the high and low-volume non-trainee groups using univariate analysis, the proportions of knees with outlier measurements for the PTA (5.3% versus 17.4%) and PSA (17.4% versus 28.3%) and the proportion of total outliers (11.8% versus 20.7%) were significantly lower in the high-volume group (all p < 0.001). The proportions of DFA (1.9% versus 6.5%), PTA (1.8% versus 5.7%), PSA (5.5% versus 12.6%), and total far outliers (3.1% versus 8.3%) were also significantly lower in the high-volume non-trainee group (all p < 0.001). Compared with the trainee group, the high-volume non-trainee group had significantly lower proportions of DFA (12.6% versus 21.6%), PTA (5.3% versus 12.0%), PSA (17.4% versus 33.3%), and total outliers (11.8% versus 22.3%) (all p < 0.001) as well as DFA (1.9% versus 3.9%; p = 0.027), PSA (5.5% versus 12.6%; p < 0.001), and total far outliers (3.1% versus 6.4%; p = 0.004). No significant differences were identified when comparing the low-volume non-trainee group and the trainee group, with the exception of PTA outliers (17.4% versus 12.0%; p = 0.041) and PTA far outliers (5.7% versus 2.6%; p = 0.033). Findings from multivariate analysis accounting for the effects of patient age, body mass index, and individual surgeon demonstrated similar results. Conclusions: Low surgical volume and trainee status were risk factors for outlier and far-outlier malalignment in primary TKA, even when accounting for differences in individual surgeon and patient characteristics. Trainee surgeons performed similarly, and certa...