Paghpappas0629

Chimeric antigen receptor T cell (CAR-T) therapy is approved for treatment of relapsed/refractory (R/R) diffuse large B cell lymphoma (DLBCL). Here we evaluate whether comorbidities, calculated using the Cumulative Illness Rating Scale (CIRS), predict survival for these patients. A retrospective chart review was performed at 4 academic institutions. All patients who underwent leukapheresis for commercial CAR-T therapy for R/R DLBCL were included. CIRS scores were calculated at the time of leukapheresis. High comorbidity was defined as either CIRS ≥7 or the presence of severe impairment (CIRS 3/4 in ≥1 system; CIRS-3+). Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method, and differences in curves were detected by the log-rank test. A total of 130 patients were analyzed, 56.9% with CIRS ≥7 and 56.2% with CIRS-3+. After a median follow-up of 13 months, the median PFS was 6.7 months, and the median OS was not reached. On univariable analysis, Eastern Cooperative Oncology Group (ECOG) performance status (PS) was associated with inferior PFS (hazard ratio [HR], 1.45; 95% confidence interval [CI], 1.03-2.05; P = .03) and OS (HR, 1.76; 95% CI, 1.17-2.64; P = .007). Higher CIRS (CIRS ≥7 or CIRS-3+) was associated with inferior OS (HR, 2.12; 95%, CI, 1.06-4.22; P = .03) and a nonsignificant trend in worse PFS (HR, 1.45; 95% CI, .87-2.44; P = .16). #link# In multivariable analyses, CIRS ≥7 or CIRS-3+ and ECOG PS maintained independent prognostic significance. Comorbidities as determined by CIRS and ECOG PS predict inferior survival in patients receiving CAR-T therapy for R/R DLBCL.

We aim to synthesize the available guidance with existing practices by Cochrane reviewers to generate an algorithm as a starting point in assisting reviewers reporting of registry records and published protocols (TRRs/PPs) use in systematic reviews of interventions.

We used existing guidance from major review bodies, assessed the current reporting of TRRs/PPs use in a sample of Cochrane reviews, and engaged in critical analysis. Independent reviewers identified and extracted textual excerpts reporting the use of trial registry records and published protocols and codes following a systematic review framework. Based on these elements, and our initial research, we created an algorithm/graphical aid to visualize initial direction.

We included 166 Cochrane systematic reviews published between August 2015 and 2016 from 48 review groups. Review authors' terminology (e.g., ongoing, terminated) varied between and within reviews. Reporting practices were diverse and inconsistent.

This is a timely investigation in an era where evidence synthesis informs health and health care decisions. Our proposed algorithm provides initial direction to systematize the reporting of TRR/PP use. We hope that the algorithm generates further discussion to enhance the transparency of TRR/PP reporting and methodological research into the complexities of using protocols in systematic reviews of interventions.

This is a timely investigation in an era where evidence synthesis informs health and health care decisions. Our proposed algorithm provides initial direction to systematize the reporting of TRR/PP use. We hope that the algorithm generates further discussion to enhance the transparency of TRR/PP reporting and methodological research into the complexities of using protocols in systematic reviews of interventions.

To systematically review the epidemiology of prerandomized run-in periods in randomized controlled trials (RCTs) of chronic diseases.

Meta-epidemiologic study of all RCTs from the four highest impact medical journals from 2011 to 2016. link2 Eligible trials included parallel RCTs that evaluated pharmacologic therapies in adults with chronic diseases with a minimum follow-up of 24weeks.

Of 262 eligible manuscripts, 48 (18.3%), representing 42 unique RCTs, included run-in periods. Run-in periods were most common in cardiovascular disease and diabetes trials. Of the 42 RCTs, in 22 patients received the experimental therapy, 15 placebo, 4 both (either sequentially or in combination), and one did not report the run-in period drug. The median run-in period duration was 28days (Q1 Q3 14 66days). Reasons for including a run-in period included ensuring eligibility criteria were met (18, 42.9%), excluding participants with nonadherence (18, 42.9%) and intolerances to therapy (15, 35.7%), and to standardize therapy prior to randomization (8, 19.0%). The median run-in completion rate was 77.4% (Q1 Q3 62.287.8%).

Run-in periods are uncommon in RCTs of chronic drug treatments and when used, their reporting is heterogeneous. Further research to improve the design, use, and reporting of run-in periods is necessary.

Run-in periods are uncommon in RCTs of chronic drug treatments and when used, their reporting is heterogeneous. Further research to improve the design, use, and reporting of run-in periods is necessary.

To investigate variation in the presence of secondary diagnosis codes in Charlson and Elixhauser comorbidity scores and assess whether including a 1-year lookback period improved prognostic adjustment by these scores individually, and combined, for 30-day mortality.

We analyzed inpatient admissions from January 1, 2007 to May 18, 2018 in Oxfordshire, UK. Comorbidity scores were calculated using secondary diagnostic codes in the diagnostic-dominant episode, and primary and secondary codes from the year before. Associations between scores and 30-day mortality were investigated using Cox models with natural cubic splines for nonlinearity, assessing fit using Akaike Information Criteria.

The 1-year lookback improved model fit for Charlson and Elixhauser scores vs. using diagnostic-dominant methods. Including selleck inhibitor , and allowing nonlinearity, improved model fit further. The diagnosis-dominant Charlson score and Elixhauser score using a 1-year lookback, and their interaction, provided the best comorbidity adjustment (reduction in AIC 761 from best single score model).

The Charlson and Elixhauser score calculated using primary and secondary diagnostic codes from 1-year lookback with secondary diagnostic codes from the current episode improved individual predictive ability. Ideally, comorbidities should be adjusted for using both the Charlson (diagnostic-dominant) and Elixhauser (1-year lookback) scores, incorporating nonlinearity and interactions for optimal confounding control.

The Charlson and Elixhauser score calculated using primary and secondary diagnostic codes from 1-year lookback with secondary diagnostic codes from the current episode improved individual predictive ability. Ideally, comorbidities should be adjusted for using both the Charlson (diagnostic-dominant) and Elixhauser (1-year lookback) scores, incorporating nonlinearity and interactions for optimal confounding control.Although Evidence-based medicine (EBM) and Patient-centered medicine (PCM) are often perceived as two conflicting paradigms that speak the language of populations and the language of individuals, respectively, both share the common objective of improving the care of individual patients. As physicians should not practice an EBM that is away from the individual patient nor a PCM that is not based on the best available evidence, it is crucial to connect and combine both movements, promoting the fruitful and natural interaction between research and care. link3 Achieving such interaction requires developing new individual-patient centric research methods. In this commentary, we propose an innovative clinical research design oriented to personalize point-of-care trials-integrating clinical research and medical care-through the incorporation of individual patients' preferences to build personalized research protocols. Building on the framework of N-of-1 studies, in "individual point-of-care trials," each protocol could be personalized for each patient so that the therapeutic objectives, the outcome variables analyzed, and the (operationalization of the) compared interventions would be based not only on the clinical and biological characteristics of each patient but also on their individual preferences, goals, and values. If patient preferences are being progressively integrated into medical practice, it makes sense that they also are incorporated into clinical trials embedded in care delivery. The proposal to perform individual point of care trials may be an optimal way to combine EBM and PCM while preserving their foundational principles, and to ensure the connection between "personalized" and "personal" care.

To describe PCORnet, a clinical research network developed for patient-centered outcomes research on a national scale.

Descriptive study of the current state and future directions for PCORnet. We conducted cross-sectional analyses of the health systems and patient populations of the 9 Clinical Research Networks and 2 Health Plan Research Networks that are part of PCORnet.

Within the Clinical Research Networks, electronic health data are currently collected from 337 hospitals, 169,695 physicians, 3,564 primary care practices, 338 emergency departments, and 1,024 community clinics. Patients can be recruited for prospective studies from any of these clinical sites. The Clinical Research Networks have accumulated data from 80 million patients with at least one visit from 2009 to 2018. The PCORnet Health Plan Research Network population of individuals with a valid enrollment segment from 2009 to 2019 exceeds 60 million individuals, who on average have 2.63years of follow-up.

PCORnet's infrastructure comprises clinical data from a diverse cohort of patients and has the capacity to rapidly access these patient populations for pragmatic clinical trials, epidemiological research, and patient-centered research on rare diseases.

PCORnet's infrastructure comprises clinical data from a diverse cohort of patients and has the capacity to rapidly access these patient populations for pragmatic clinical trials, epidemiological research, and patient-centered research on rare diseases.CD4+ T lymphocytes are key mediators of tissue damage after ischemic stroke. However, their infiltration kinetics and interactions with other immune cells in the delayed phase of ischemia remain elusive. We hypothesized that CD4+ T cells facilitate delayed autoreactive B cell responses in the brain, which have been previously linked to post-stroke cognitive impairment (PSCI). Therefore, we treated myelin oligodendrocyte glycoprotein T cell receptor transgenic 2D2 mice of both sexes with anti-CD4 antibody following 60-minute middle cerebral artery occlusion and assessed lymphocyte infiltration for up to 72 days. Anti-CD4-treatment eliminated CD4+ T cells from the circulation and ischemic brain for 28 days and inhibited B cell infiltration into the brain, particularly in animals with large infarcts. Absence of CD4+ T cells did not influence infarct maturation or survival. Once the CD4+ population recovered in the periphery, both CD4+ T and B lymphocytes entered the infarct site forming follicle-like structures. Additionally, we provide further evidence for PSCI that could be attenuated by CD4 depletion. Our findings demonstrate that CD4+ T cells are essential in delayed B cell infiltration into the ischemic brain after stroke. Importantly, lymphocyte infiltration after stroke is a long-lasting process. As CD4 depletion improved cognitive functions in an experimental set-up, these findings set the stage to elaborate more specific immune modulating therapies in treating PSCI.