Citations

Abstract Chronic granulomatous disease (CGD) is a primary immunodeficiency characterized by life-threatening infections and inflammatory conditions. Hematopoietic cell transplantation (HCT) is the definitive treatment for CGD, but questions remain regarding patient selection and impact of active disease on transplant outcomes. We performed a multi-institutional retrospective and prospective study of 391 patients with CGD treated either conventionally (non-HCT) enrolled from 2004 to 2018 or with HCT from 1996 to 2018. Median follow-up after HCT was 3.7 years with a 3-year overall survival of 82% and event-free survival of 69%. In a multivariate analysis, a Lansky/Karnofsky score <90 and use of HLA-mismatched donors negatively affected survival. Age, genotype, and oxidase status did not affect outcomes. Before HCT, patients had higher infection density, higher frequency of noninfectious lung and liver diseases, and more steroid use than conventionally treated patients; however, these issues did not adversely affect HCT survival. Presence of pre-HCT inflammatory conditions was associated with chronic graft-versus-host disease. Graft failure or receipt of a second HCT occurred in 17.6% of the patients and was associated with melphalan-based conditioning and/or early mixed chimerism. At 3 to 5 years after HCT, patients had improved growth and nutrition, resolved infections and inflammatory disease, and lower rates of antimicrobial prophylaxis or corticosteroid use compared with both their baseline and those of conventionally treated patients. HCT leads to durable resolution of CGD symptoms and lowers the burden of the disease. Patients with active infection or inflammation are candidates for transplants; HCT should be considered before the development of comorbidities that could affect performance status. This trial was registered at www.clinicaltrials.gov as #NCT02082353.

PURPOSE Increased awareness of the distinct tumor biology for adolescents and young adults (AYAs) with cancer has led to improvement in outcomes for this population. However, in cholangiocarcinoma (CCA), a paucity of data exist on the AYA population. To our knowledge, we present the largest study to date on AYA disease biology, treatment patterns, and survival outcomes in CCA. METHODS A multi-institutional cohort of patients with CCA diagnosed with intrahepatic cholangiocarcinoma (ICC) or extrahepatic cholangiocarcinoma (ECC) was used for analysis. Retrospective chart review was conducted on patients who were 50 years old and younger (young; n = 124) and older than 50 years (older; n = 723). RESULTS Among 1,039 patients screened, 847 patients met eligibility (72% ICC, 28% ECC). Young patients had a larger median tumor size at resection compared with older patients (4.2 v 3.6 cm; P = .048), more commonly had N1 disease (65% v 43%; P = .040), and were more likely to receive adjuvant therapy (odds ratio, 4.0; 95% CI, 1.64 to 9.74). Tumors of young patients were more likely to harbor an FGFR2 fusion, BRAF mutation, or ATM mutation ( P < .05 for each). Young patients were more likely to receive palliative systemic therapy (96% v 69%; P < .001), targeted therapy (23% v 8%; P < .001), and treatment on a clinical trial (31% v 19%; P = .004). Among patients who presented with advanced disease, young patients had a higher median overall survival compared with their older counterparts (17.7 v 13.5 months; 95% CI, 12.6 to 22.6 v 11.4 to 14.8; P = .049). CONCLUSION Young patients with CCA had more advanced disease at resection, more commonly received both adjuvant and palliative therapies, and demonstrated improved survival compared with older patients. Given the low clinical trial enrollment and poor outcomes among some AYA cancer populations, data to the contrary in CCA are highly encouraging.

PURPOSE BMI affects breast cancer risk and prognosis. In contrast to cytotoxic chemotherapy, CDK4/6 inhibitors are given at a fixed dose, irrespective of BMI or weight. This preplanned analysis of the global randomized PALLAS trial investigates the impact of BMI on the side-effect profile, treatment adherence, and efficacy of palbociclib. METHODS Patients were categorized at baseline according to WHO BMI categories. Neutropenia rates were assessed with univariable and multivariable logistic regression. Time to early discontinuation of palbociclib was analyzed with Fine and Gray competing risk models. Unstratified Cox models were used to investigate the association between BMI category and time to invasive disease-free survival (iDFS). 95% CIs were derived. RESULTS Of 5,698 patients included in this analysis, 68 (1.2%) were underweight, 2,082 (36.5%) normal weight, 1,818 (31.9%) overweight, and 1,730 (30.4%) obese at baseline. In the palbociclib arm, higher BMI was associated with a significant decrease in neutropenia (unadjusted odds ratio for 1-unit change, 0.93; 95% CI, 0.91 to 0.94; adjusted for age, race ethnicity, region, chemotherapy use, and Eastern Cooperative Oncology Group at baseline, 0.93; 95% CI, 0.92 to 0.95). This translated into a significant decrease in treatment discontinuation rate with higher BMI (adjusted hazard ratio [HR] for 10-unit change, 0.75; 95% CI, 0.67 to 0.83). There was no significant improvement in iDFS with the addition of palbociclib to ET in any weight category (normal weight HR, 0.84; 95% CI, 0.63 to 1.12; overweight HR, 1.10; 95% CI, 0.82 to 1.49; and obese HR, 0.95; 95% CI, 0.69 to 1.30) in this analysis early in follow-up (31 months). CONCLUSION This preplanned analysis of the PALLAS trial demonstrates a significant impact of BMI on side effects, dose reductions, early treatment discontinuation, and relative dose intensity. Additional long-term follow-up will further evaluate whether BMI ultimately affects outcome.

Abstract Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both symbolic and statistical methods, as well as highlight the need for federated annotation and evaluation to resolve several pitfalls encountered in the course of these efforts.

Abstract Myelodysplastic neoplasms (MDS) are a collection of hematopoietic disorders with widely variable prognoses and treatment options. Accurate pathologic diagnoses present challenges because of interobserver variability in interpreting morphology and quantifying dysplasia. We compared local clinical site diagnoses with central, adjudicated review from 918 participants enrolled in the ongoing National Heart, Lung, and Blood Institute National MDS Natural History Study, a prospective observational cohort study of participants with suspected MDS or MDS/myeloproliferative neoplasms (MPNs). Locally, 264 (29%) were diagnosed as having MDS, 15 (2%) MDS/MPN overlap, 62 (7%) idiopathic cytopenia of undetermined significance (ICUS), 0 (0%) acute myeloid leukemia (AML) with &lt;30% blasts, and 577 (63%) as other. Approximately one-third of cases were reclassified after central review, with 266 (29%) diagnosed as MDS, 45 (5%) MDS/MPN overlap, 49 (5%) ICUS, 15 (2%) AML with &lt;30%, and 543 (59%) as other. Site miscoding errors accounted for more than half (53%) of the local misdiagnoses, leaving a true misdiagnosis rate of 15% overall, 21% for MDS. Therapies were reported in 37% of patients, including 43% of patients with MDS, 49% of patients with MDS/MPN, and 86% of patients with AML with &lt;30% blasts. Treatment rates were lower (25%) in cases with true discordance in diagnosis compared with those for whom local and central diagnoses agreed (40%), and receipt of inappropriate therapy occurred in 7% of misdiagnosed cases. Discordant diagnoses were frequent, which has implications for the accuracy of study-related and national registries and can lead to inappropriate therapy. This trial was registered at www.clinicaltrials.gov as #NCT05074550.

To understand why US patients refused participation in hospital-at-home (H@H) during the coronavirus disease 2019 Public Health Emergency, eligible adult patients seen at 2 Mayo Clinic sites, Mayo Clinic Health System—Northwest Wisconsin region (NWWI) and Mayo Clinic Florida (MCF), from August 2021 through March 2022, were invited to participate in a convergent-parallel study. Quantitative associations between H@H participation status and patient baseline data at hospital admission were investigated. H@H patients were more likely to have a Mayo Clinic patient portal at baseline ( P-value: .014), indicating a familiarity with telehealth. Patients who refused were more likely to be from NWWI ( P-value < .001) and have a higher Epic Deterioration Index score ( P-value: .004). The groups also had different quarters (in terms of fiscal calendar) of admission ( P-value: .040). Analyzing qualitative interviews (n = 13) about refusal reasons, 2 themes portraying the quantitative associations emerged: lack of clarity about H@H and perceived domestic challenges. To improve access to H@H and increase patient recruitment, improved education about the dynamics of H@H, for both hospital staff and patients, and inclusive strategies for navigating domestic barriers and diagnostic challenges are needed.

AbstractBackgroundInfertility has been linked with an increased risk of sexual dysfunction in reproductive-aged women, with longer periods of infertility associated with a greater risk.AimThe study’s aim was to examine whether a history of infertility treatment in women is linked to sexual dysfunction during midlife.MethodsThe cross-sectional study was conducted among sexually active women, between the ages of 45 and 65 years, who sought consultation at the women’s health clinics at a US tertiary care center. History of infertility treatment was assessed with a single question that asked participants if they were treated for infertility in the past. The association between a history of infertility treatment and sexual dysfunction—which was diagnosed by a combination of Female Sexual Function Index score ≤26.55 and Female Sexual Distress Scale–Revised score ≥11—was assessed in a multivariable logistic regression model that adjusted for multiple confounders.OutcomesThe primary outcome was sexual dysfunction in midlife women.ResultsThe analysis included 5912 women, with a mean age of 54.1 years. Nearly 16% of women reported receiving treatment for infertility. More than half the women (55%) had sexual dysfunction: 56.3% of those with previous fertility treatments and 54.4% of those without any fertility treatment (P = .3). Receiving treatment for infertility in the younger years did not significantly increase the odds of sexual dysfunction in midlife in univariate (odds ratio, 1.08; 95% CI, 0.94-1.24; P = .3) and multivariable analyses (odds ratio, 1.11; 95% CI, 0.96-1.29; P = .17).Clinical ImplicationsWhile infertility is known to be predictive of sexual dysfunction in women during their reproductive years, there was no association between a history of infertility treatment and sexual dysfunction in midlife women in the current study.Strengths and LimitationsThe study used validated questionnaires accounting for sexual complaints and distress and adjusted for multiple confounding factors. Limitations include the selection bias introduced by the study of women presenting for evaluation of sexual dysfunction, which may have been a result of factors stronger than the influence of infertility. Other limitations include the study’s cross-sectional nature with suboptimal racial and ethnic representation.ConclusionAlthough infertility is commonly associated with female sexual dysfunction in women of reproductive age, the association was not present in midlife women in the current study.

AbstractObjectiveTo evaluate the impact of a virtual registered nurse (ViRN) model on safety and care outcomes. ViRN is a telemedicine intervention that enables an experienced virtual nurse to assist the in‐person care team in providing care to patients.Data Sources and Study SettingElectronic health records data were utilized from the Mayo Clinic during the intervention (December 2020–November 2021) and historical periods (December 2018–November 2019). ViRN was implemented on general medical units at the Mayo Clinic Rochester. We used general medical units at the Mayo Clinic Arizona as the comparison group.Study DesignThis study used a difference‐in‐differences design to evaluate the impact of ViRN compared to usual care on transfer to the intensive care unit (ICU), inpatient mortality, and length of stay (LOS). We used logistic regression for transfer to the ICU and inpatient mortality and negative binomial regression for LOS. We controlled for demographics, patient interaction with the health system, clinical characteristics, and admission characteristics. We clustered standard errors to account for patients who have multiple admissions during the study period.Principal FindingsThere were no significant differences for transfer to the ICU (average marginal effect (AME) −0.08 percentage point [95% confidence interval (CI): −1.34, 1.18]), inpatient mortality (AME 0.43 percentage point [95% CI: −0.33, 1.18]), or LOS (AME −0.20 days [95% CI: −0.57, 0.17]). The findings were mostly consistent across the sensitivity analyses.ConclusionsOur results suggest that ViRN led to similar outcomes as usual care in general medical units. These findings support the potential to develop more advanced models of ViRN at the Mayo Clinic and the dissemination of the ViRN model to other systems. In the context of staffing shortages and other disruptions to the delivery of nursing care, it is critical to understand whether new models like ViRN provide nurse staffing alternatives without negatively affecting outcomes.