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PURPOSE Survival for patients with melanoma has recently improved. The propensity of melanoma to metastasize to the brain remains a common and serious feature of this disease. The purposes of this study were to evaluate prognostic factors for patients with newly diagnosed melanoma brain metastases (MBMs) in a large cohort treated with modern multimodal therapies, compare those results with those in prior eras, and update the Melanoma Graded Prognostic Assessment (GPA). METHODS Univariable and multivariable (MVA) analyses of prognostic factors and treatments associated with survival were performed on 1,796 patients with newly diagnosed MBM treated between January 01, 2015, and December 31, 2021, using a multi-institutional retrospective database. Multiple imputation was used to address missingness of potential predictors. Significant variables in combined MVA were used to update the Melanoma GPA. Comparisons were made with legacy cohorts. RESULTS Median survivals for cohorts A (1985-2007, n = 481), B (2006-2015, n = 823), and C (2015-2021, n = 1,796) were 6.7, 9.8, and 16.6 months and median follow-up times were 40.1, 43.6, and 48.8 months, respectively. In combined MVA, significant prognostic factors for survival were higher Karnofsky Performance Status, fewer MBMs, absence of extracranial metastases, lower serum lactate dehydrogenase, and no immunotherapy before MBM. These factors were incorporated into the updated Melanoma GPA. The combined median and 3-year survivals for patients with GPA 0-1, 1.5-2, and 2.5-4.0 were 5.4, 13.2, and 43.2 months and 12.4%, 28.8%, and 51.6%, respectively. CONCLUSION Prognostic factors have changed and survival has improved for patients with MBM but varies widely by GPA. The updated Melanoma GPA calculator (BrainMetGPA), available free online, can be used to estimate survival, individualize treatment, stratify clinical trials, guide surveillance, and augment clinical trial eligibility. Multidisciplinary treatment is essential. Trials are needed to elucidate the optimal sequencing of various therapeutic modalities.

Background Falls in people with multiple sclerosis (pwMS) lead to morbidity and expense. Objective Identify clinical metrics associated with falls. Methods Eighty-six pwMS completed fall surveys, timed 25-foot walk (T25FW), and motion analysis with Clario Opal devices. Logistic regression models were created. Results Median age was 54.5 years (range 21–73), 62% (53) were female. The cohort included 58% with relapsing (50) and 42% with progressive MS (36). Those who reported falling in the last year were older (median age 58 vs 52.5, p = .03) and had a higher Patient Determined Disease Step (PDDS) score (median 3 vs 1, p < .0001). Falls were associated with worse balance metrics including sway area (median 2.3 degrees 2 vs 1.2, p = .01), jerk (median 3.3 m 2 /s 5 vs 1.6, p = .005), and slower T25FW (median 11.5 s vs 8; p < .0001). A multivariable regression model based on gait aid use and T25FW time >10.8 s (c = 0.80) was derived. Having both features portended a probability of falling of 0.97, while having neither, a probability of 0.26. Conclusions Falls in pwMS are more frequent in patients who are older, have higher PDDS, slower walking, and worse balance. Gait aid use and T25FW >10.8 s were strongly associated with falls in the past year.

Key Points In phospholipase A2 receptor-membranous nephropathy, clinical variables and antibody levels over 3 or 6 months of treatment were predictors of remission at 1 year. Prediction models at 3 and 6 months had similar performance predicting remission, with the 3-month model allowing for earlier assessment of response. The 3-month and 6-month prediction models could be applied in those treated with supportive therapy, rituximab, calcineurin inhibitors, or cyclophosphamide. Background In patients with antiphospholipase A2 receptor antibody–associated membranous nephropathy, there is currently no accepted method to predict an individual's probability of remission after treatment with immunosuppression or supportive therapy using changes in antibody levels and clinical variables during the first 3–6 months of therapy. Methods Using a cohort of 187 patients from the Glomérulopathie extramembraneuse rituximab, Membranous Nephropathy Trial of Rituximab, and Sequential Treatment with Tacrolimus and Rituximab Versus Alternating Corticosteroids and Cyclophosphamide in primary Membranous Nephropathy clinical trials with antibody levels at baseline ≥14 RU/ml, we derived logistic regression models to predict proteinuria remission at 12 months that can be used at baseline or after 3 or 6 months of treatment. Treatment exposures in the trials included supportive therapy, rituximab, calcineurin inhibitors, and cyclophosphamide. Predictors in the models included male sex and baseline and changes in serum albumin, proteinuria, and antibody levels, with or without changes in eGFR. Results Proteinuria remission at 12 months was achieved in 107 patients. Compared with the model at baseline, the 3-month and 6-month models had better model fit with lower Akaike information criterion (186/158 versus 225) and higher R 2 (52.7%/62.4% versus 25.8%), better discrimination with higher C-statistic (0.87 and 0.91 versus 0.75, P < 0.001), and better calibration with lower integrated calibration index (0.89%/2.22% versus 2.51%). The 3-month and 6-month models had no consistent difference in prediction performance, and decision curve analysis demonstrated similar net benefit for treatment decisions based on either model up to a threshold probability of 31%. Prediction performance was similar after internal validation using optimism correction. Prediction performance was maintained within subgroups of different treatment regimens, including supportive therapy, rituximab, calcineurin inhibitors, and cyclophosphamide. Conclusions Either the 3-month or 6-month models can be used in patients with antiphospholipase A2 receptor antibody associated membranous nephropathy after 3 or 6 months of treatment with a variety of immunosuppression or supportive therapy to predict remission status at 12 months.

Ewing sarcoma and osteosarcoma constitute 36% of all primary bone cancers. However, these 2 subtypes represent the most commonly diagnosed bone cancer types in the pediatric and adolescent population. Although still largely unknown, certain genetic mutations, rearrangements, and/or predisposition syndromes likely play a role in the pathogenesis of bone cancer. Osteosarcoma may also develop as a direct result of the long-term side effects of radiation therapy. With the implementation of a multimodality approach to treatment, including multiagent neoadjuvant and adjuvant chemotherapy regimens, targeted therapy options, surgery, and radiation, individuals with Ewing sarcoma and osteosarcoma are showing higher cure rates and improved overall survival. The NCCN Guidelines for Bone Cancer provide a consensus and evidence-based framework for the workup, management, and surveillance of local and recurrent/metastatic disease.