Psychological experience and coping strategies of patients in the Northeast US delaying care for infertility during the COVID-19 pandemic.

BACKGROUND: On March 17, 2020 an expert ASRM task force recommended the temporary suspension of new, non-urgent fertility treatments during an ongoing world-wide pandemic of Covid-19. We surveyed at the time of resumption of fertility care the psychological experience and coping strategies of patients pausing their care due to Covid-19 and examined which factors were associated and predictive of resilience, anxiety, stress and hopefulness. METHODS: Cross sectional cohort patient survey using an anonymous, self-reported, single time, web-based, HIPPA compliant platform (REDCap). Survey sampled two Northeast academic fertility practices (Yale Medicine Fertility Center in CT and Montefiore's Institute for Reproductive Medicine and Health in NY). Data from multiple choice and open response questions collected demographic, reproductive history, experience and attitudes about Covid-19, prior infertility treatment, sense of hopefulness and stress, coping strategies for mitigating stress and two validated psychological surveys to assess anxiety (six-item short-form State Trait Anxiety Inventory (STAl-6)) and resilience (10-item Connor-Davidson Resilience Scale, (CD-RISC-10). RESULTS: Seven hundred thirty-four patients were sent invitations to participate. Two hundred fourteen of 734 (29.2%) completed the survey. Patients reported their fertility journey had been delayed a mean of 10 weeks while 60% had been actively trying to conceive > 1.5 years. The top 5 ranked coping skills from a choice of 19 were establishing a daily routine, going outside regularly, exercising, maintaining social connection via phone, social media or Zoom and continuing to work. Having a history of anxiety (p < 0.0001) and having received oral medication as prior infertility treatment (p < 0.0001) were associated with lower resilience. Increased hopefulness about having a child at the time of completing the survey (p < 0.0001) and higher resilience scores (p < 0.0001) were associated with decreased anxiety. Higher reported stress scores (p < 0.0001) were associated with increased anxiety. Multiple multivariate regression showed being non-Hispanic black (p = 0.035) to be predictive of more resilience while variables predictive of less resilience were being a full-time homemaker (p = 0.03), having received oral medication as prior infertility treatment (p = 0.003) and having higher scores on the STAI-6 (< 0.0001). CONCLUSIONS: Prior to and in anticipation of further pauses in treatment the clinical staff should consider pretreatment screening for psychological distress and provide referral sources. In addition, utilization of a patient centered approach to care should be employed.

Harnessing electronic medical records to advance research on multiple sclerosis.

BACKGROUND: Electronic medical records (EMR) data are increasingly used in research, but no studies have yet evaluated similarity between EMR and research-quality data and between characteristics of an EMR multiple sclerosis (MS) population and known natural MS history. OBJECTIVES: To (1) identify MS patients in an EMR system and extract clinical data, (2) compare EMR-extracted data with gold-standard research data, and (3) compare EMR MS population characteristics to expected MS natural history. METHODS: Algorithms were implemented to identify MS patients from the University of California San Francisco EMR, de-identify the data and extract clinical variables. EMR-extracted data were compared to research cohort data in a subset of patients. RESULTS: We identified 4142 MS patients via search of the EMR and extracted their clinical data with good accuracy. EMR and research values showed good concordance for Expanded Disability Status Scale (EDSS), timed-25-foot walk, and subtype. We replicated several expected MS epidemiological features from MS natural history including higher EDSS for progressive versus relapsing-remitting patients and for male versus female patients and increased EDSS with age at examination and disease duration. CONCLUSION: Large real-world cohorts algorithmically extracted from the EMR can expand opportunities for MS clinical research.

Long-term evolution of multiple sclerosis disability in the treatment era.

OBJECTIVE: To characterize the accrual of long-term disability in a cohort of actively treated multiple sclerosis (MS) patients and to assess whether clinical and magnetic resonance imaging (MRI) data used in clinical trials have long-term prognostic value. METHODS: This is a prospective study of 517 actively managed MS patients enrolled at a single center. RESULTS: More than 91% of patients were retained, with data ascertained up to 10 years after the baseline visit. At this last assessment, neurologic disability as measured by the Expanded Disability Status Scale (EDSS) was stable or improved compared to baseline in 41% of patients. Subjects with no evidence of disease activity (NEDA) by clinical and MRI criteria during the first 2 years had long-term outcomes that were no different from those of the cohort as a whole. 25-OH vitamin D serum levels were inversely associated with short-term MS disease activity; however, these levels had no association with long-term disability. At a median time of 16.8 years after disease onset, 10.7% (95% confidence interval [CI] = 7.2-14%) of patients reached an EDSS ≥ 6, and 18.1% (95% CI = 13.5-22.5%) evolved from relapsing MS to secondary progressive MS (SPMS). INTERPRETATION: Rates of worsening and evolution to SPMS were substantially lower when compared to earlier natural history studies. Notably, the NEDA 2-year endpoint was not a predictor of long-term stability. Finally, the data call into question the utility of annual MRI assessments as a treat-to-target approach for MS care. Ann Neurol 2016;80:499-510.

Estimate of the incidence of PANDAS and PANS in 3 primary care populations.

Objective: Pediatric Autoimmune Neuropsychiatric Disorder Associated with Streptococcal infection (PANDAS) and Pediatric Acute-Onset Neuropsychiatric syndrome (PANS) are presumed autoimmune complications of infection or other instigating events. To determine the incidence of these disorders, we performed a retrospective review for the years 2017-2019 at three academic medical centers. Methods: We identified the population of children receiving well-child care at each institution. Potential cases of PANS and PANDAS were identified by including children age 3-12 years at the time they received one of five new diagnoses: avoidant/restrictive food intake disorder, other specified eating disorder, separation anxiety disorder of childhood, obsessive-compulsive disorder, or other specified disorders involving an immune mechanism, not elsewhere classified. Tic disorders was not used as a diagnostic code to identify cases. Data were abstracted; cases were classified as PANDAS or PANS if standard definitions were met. Results: The combined study population consisted of 95,498 individuals. The majority were non-Hispanic Caucasian (85%), 48% were female and the mean age was 7.1 (SD 3.1) years. Of 357 potential cases, there were 13 actual cases [mean age was 6.0 (SD 1.8) years, 46% female and 100% non-Hispanic Caucasian]. The estimated annual incidence of PANDAS/PANS was 1/11,765 for children between 3 and 12 years with some variation between different geographic areas. Conclusion: Our results indicate that PANDAS/PANS is a rare disorder with substantial heterogeneity across geography and time. A prospective investigation of the same question is warranted.

Multi-Dimensional Flow Cytometry Analyses Reveal a Dichotomous Role for Nitric Oxide in Melanoma Patients Receiving Immunotherapy.

Phenotyping of immune cell subsets in clinical trials is limited to well-defined phenotypes, due to technological limitations of reporting flow cytometry multi-dimensional phenotyping data. We developed a multi-dimensional phenotyping analysis tool and applied it to detect nitric oxide (NO) levels in peripheral blood immune cells before and after adjuvant ipilimumab co-administration with a peptide vaccine in melanoma patients. We analyzed inhibitory and stimulatory markers for immune cell phenotypes that were felt to be important in the NO analysis. The pipeline allows visualization of immune cell phenotypes without knowledge of clustering techniques and to categorize cells by association with relapse-free survival (RFS). Using this analysis, we uncovered the potential for a dichotomous role of NO as a pro- and anti-melanoma factor. NO was found in subsets of immune-suppressor cells associated with shorter-term (≤ 1 year) RFS, whereas NO was also present in immune-stimulatory effector cells obtained from patients with significant longer-term (> 1 year) RFS. These studies provide insights into the cell-specific immunomodulatory role of NO. The methods presented herein can be applied to monitor the pro- and anti-tumor effects of a variety of immune-based therapeutics in cancer patients. Clinical Trial Registration Number: NCT00084656 (https://clinicaltrials.gov/ct2/show/NCT00084656).

Multidimensional reduction of multicentric cohort heterogeneity: An alternative method to increase statistical power and robustness.

Modern clinical research takes advantage of multicentric cohorts to increase sample size and gain in statistical power. However, combining individuals from different recruitment centers provides heterogeneity in the dataset that needs to be accounted for to obtain robust results. Sophisticated statistical multivariate models adjusting for center effect can be implemented, but they can become unstable and can be complex to interpret with the increasing number of covariates to consider. Here, we present a multidimensional reduction technique to identify heterogeneity in a French multicentric cohort of hematopoietic stem cell transplantations and characterize a homogeneous subgroup prior to performing simple statistical univariate analyses. The exclusion of outliers allowed the identification of two genetic factors associated with post-transplantation overall survival. We therefore provide proof-of-concept that a sample size reduction method can efficiently account for heterogeneity and center effect in multicentric cohorts while increasing statistical power and robustness for discovery of new association signals.