Citations

Improving long-term allograft survival and minimizing recipient morbidity is of key importance in all of transplantation. Improved matching of classical HLA molecules and avoiding HLA donor-specific antibody has been a major focus; however, emerging data suggest the relevance of nonclassical HLA molecules, major histocompatibility complex class I chain-related gene A (MICA) and B, in transplant outcomes. The purpose of this review is to discuss the structure, function, polymorphisms, and genetics of the MICA molecule and relates this to clinical outcomes in solid organ and hematopoietic stem cell transplantation. The tools available for genotyping and antibody detection will be reviewed combined with a discussion of their shortcomings. Although data supporting the relevance of MICA molecules have accumulated, key knowledge gaps exist and should be addressed before widespread implementation of MICA testing for recipients pre- or posttransplantation.

BACKGROUND: Surgical intervention remains the cornerstone of a multidisciplinary approach in the treatment of colorectal liver metastases (CLM). Nevertheless, patient outcomes vary greatly. While predictive tools can assist decision-making and patient counseling, decades of efforts have yet to result in generating a universally adopted tool in clinical practice. STUDY DESIGN: An international collaborative database of CLM patients who underwent surgical therapy between 2000 and 2018 was used to select 1,004 operations for this study. Two different machine learning methods were applied to construct 2 predictive models for recurrence and death, using 128 clinicopathologic variables: gradient-boosted trees (GBTs) and logistic regression with bootstrapping (LRB) in a leave-one-out cross-validation. RESULTS: Median survival after resection was 47.2 months, and disease-free survival was 19.0 months, with a median follow-up of 32.0 months in the cohort. Both models had good predictive power, with GBT demonstrating a superior performance in predicting overall survival (area under the receiver operating curve [AUC] 0.773, 95% CI 0.743 to 0.801 vs LRB: AUC 0.648, 95% CI 0.614 to 0.682) and recurrence (AUC 0.635, 95% CI 0.599 to 0.669 vs LRB: AUC 0.570, 95% CI 0.535 to 0.601). Similarly, better performances were observed predicting 3- and 5-year survival, as well as 3- and 5-year recurrence, with GBT methods generating higher AUCs. CONCLUSIONS: Machine learning provides powerful tools to create predictive models of survival and recurrence after surgery for CLM. The effectiveness of both machine learning models varies, but on most occasions, GBT outperforms LRB. Prospective validation of these models lays the groundwork to adopt them in clinical practice.

Objective The aim of this study was to determine inpatient health care utilization in an incident cohort of patients with systemic lupus erythematosus (SLE) compared with the general population. Methods This was a population-based cohort study in the upper Midwest, United States. We included patients fulfilling the European League Against Rheumatism/American College of Rheumatology SLE classification criteria between 1995 and 2018. They were 1:1 age-, sex-, county-matched with individuals without SLE. All hospital admissions and emergency department (ED) visits were electronically retrieved for 1995–2020. Rates for hospital admission, length of stay, readmission, ED visits, and discharge destination were compared between groups. Results Three hundred forty-one patients with SLE and 341 comparators without SLE were included (mean age, 48.6 years at diagnosis; 79.2% female). Rates of hospitalization for patients with SLE and comparators were 29.8 and 9.9 per 100 person-years, respectively. These differences were present across sexes and age groups. Hospitalization rates were higher in patients with SLE after diagnosis and remained higher than comparators for the first 15 years of the disease. Patients with SLE were more likely than comparators to visit the ED (hazard ratio, 2.71; 95% confidence interval, 2.05–3.59). Readmission rates (32% vs. 21%, p = 0.017) were higher in patients with SLE. Length of stay and discharge destination were similar between both groups. Conclusion Patients with SLE were more likely to be hospitalized and to visit the ED than individuals without SLE, highlighting important inpatient care needs. Increased hospitalization rates were observed in both male and female patients and all age groups.

ObjectiveTo determine the association between race/ethnicity and COVID‐19 outcomes in individuals with systemic lupus erythematosus (SLE).MethodsIndividuals with SLE from the US with data entered into the COVID‐19 Global Rheumatology Alliance registry between March 24, 2020 and August 27, 2021 were included. Variables included age, sex, race, and ethnicity (White, Black, Hispanic, other), comorbidities, disease activity, pandemic time period, glucocorticoid dose, antimalarials, and immunosuppressive drug use. The ordinal outcome categories were: not hospitalized, hospitalized with no oxygenation, hospitalized with any ventilation or oxygenation, and death. We constructed ordinal logistic regression models evaluating the relationship between race/ethnicity and COVID‐19 severity, adjusting for possible confounders.ResultsWe included 523 patients; 473 (90.4%) were female and the mean ± SD age was 46.6 ± 14.0 years. A total of 358 patients (74.6%) were not hospitalized; 40 patients (8.3%) were hospitalized without oxygen, 64 patients (13.3%) were hospitalized with any oxygenation, and 18 (3.8%) died. In a multivariable model, Black (odds ratio [OR] 2.73 [95% confidence interval (95% CI) 1.36–5.53]) and Hispanic (OR 2.76 [95% CI 1.34–5.69]) individuals had higher odds of more severe outcomes than White individuals.ConclusionBlack and Hispanic individuals with SLE experienced more severe COVID‐19 outcomes, which is consistent with findings in the US general population. These results likely reflect socioeconomic and health disparities and suggest that more aggressive efforts are needed to prevent and treat infection in this population.

Objective There is a paucity of population‐based studies investigating the epidemiology of lupus nephritis (LN) in the US and long‐term secular trends of the disease and its outcomes. We aimed to examine the epidemiology of LN in a well‐defined 8‐county region in the US. Methods Patients with incident LN between 1976 and 2018 in Olmsted County, Minnesota (1976–2009) and an 8‐county region in southeast Minnesota (2010–2018) were identified. Age‐ and sex‐specific incidence rates and point prevalence over 4 decades, adjusted to the projected 2000 US population, were determined. Standardized mortality ratios (SMRs), survival rates, and time to end‐stage renal disease (ESRD) were estimated. Results There were 72 patients with incident LN between 1976 and 2018, of whom 76% were female and 69% were non‐Hispanic White. Mean ± SD age at diagnosis was 38.4 ± 16.24 years. Average annual LN incidence per 100,000 population between 1976 and 2018 was 1.0 (95% CI 0.8–1.3) and was highest in patients ages 30–39 years. Between the 1976–1989 and 2000–2018 time periods, overall incidence of LN increased from 0.7 to 1.3 per 100,000, but this was not statistically significant. Estimated LN prevalence increased from 16.8 per 100,000 in 1985 to 21.2 per 100,000 in 2015. Patients with LN had an SMR of 6.33 (95% CI 3.81–9.89), with no improvement in the mortality gap in the last 4 decades. At 10 years, survival was 70%, and 13% of LN patients had ESRD. Conclusion The incidence and prevalence of LN in this area increased in the last 4 decades. LN patients have poor outcomes, with high rates of ESRD and mortality rates 6 times that of the general population.

AbstractBackgroundResection of colorectal liver metastasis (CLM) is beneficial when feasible. However, the benefit of second hepatectomy for hepatic recurrence in CLM remains unclear.MethodsThe Colorectal Liver Operative Metastasis International Collaborative retrospectively examined 1004 CLM cases from 2000 to 2018 from a total of 953 patients. Hepatic recurrence after initial hepatectomy was identified in 218 patients. Kaplan–Meier analysis was performed for overall survival (OS) and recurrence‐free survival (RFS). Propensity score matching (PSM) was performed to offset selection bias. Cox proportional‐hazards regression was performed to identify risk factors associated with OS.ResultsA total of 51 patients underwent second hepatectomy. Unadjusted median OS was 60.1 months in repeat‐hepatectomy versus 38.3 months in the single‐hepatectomy group (p = 0.015). In the PSM population, median OS remained significantly better in the repeat‐hepatectomy group (60.1 vs. 33.1 months; p = 0.0023); median RFS was 12.4 months for the repeat‐hepatectomy group, versus 9.8 months in the single‐hepatectomy group (p = 0.0050). Repeat hepatectomy was associated with lower risk of death (hazard ratio: 0.283; p = 0.000012). Obesity, tobacco use, and high intraoperative blood loss were associated with significant risk of death (p < 0.05).ConclusionIn CLM with hepatic recurrence, second hepatectomy was beneficial for OS. With PSM, the OS benefit of performing a second hepatectomy remained significant.

ObjectiveSome patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID‐19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID‐19 ARDS in this population and to create a simple risk score calculator for use in clinical settings.MethodsData were derived from the COVID‐19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID‐19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier.ResultsThe study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67‐0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%‐83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator.ConclusionWe were able to predict ARDS with good sensitivity using information readily available at COVID‐19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID‐19 disease progression.

Background Oncolytic virotherapy (OV) represents a method to treat a variety of solid tumors by inducing antitumor immune responses. While this therapy has been extremely efficacious in preclinical models, translating these successes into human patients has proven challenging. One of the major reasons for these failures is the existence of immune-regulatory mechanisms, which dampen the efficacy of virally induced antitumor immunity. Unfortunately, the full extent of these immune-regulatory pathways remains unclear. Methods To address this issue, we generated a doubly recombinant, oncolytic myxoma virus which expresses both a soluble fragment of programmed cell death protein 1 (PD1) and an interleukin 12 (IL-12) fusion protein (vPD1/IL-12 (virus-expressing PD1 and IL-12)). We then tested the molecular impact and therapeutic efficacy of this construct in multiple models of disseminated disease to identify novel pathways, which are associated with poor therapeutic outcomes. Results Our results demonstrate that vPD1/IL-12 causes robust inflammation during therapy including inducing high levels of tumor necrosis factor (TNF). Surprisingly, although expression of TNF has generally been assumed to be beneficial to OV, the presence of this TNF appears to inhibit therapeutic efficacy by reducing intratumoral T-cell viability. Likely because of this, disruption of the TNF pathway, either through genetic knockout or antibody-based blockade, significantly enhances the overall outcomes of vPD1/IL-12-based therapy that allows for the generation of complete cures in normally non-responsive models. Conclusions These data suggest that some aspects of OV-induced inflammation might represent a double-edged sword during therapy and that specific blockade of TNF might enhance the efficacy of these treatments.