Utility of cell-based vaccines as cancer therapy: Systematic review and meta-analysis

Cell-based therapeutic cancer vaccines use autologous patient-derived tumor cells, allogeneic cancer cell lines or autologous antigen presenting cells to mimic the natural immune process and stimulate an adaptive immune response against tumor antigens. The primary objective of this study is to perform a systematic literature review with an embedded meta-analysis of all published Phase 2 and 3 clinical trials of cell-based cancer vaccines in human subjects. The secondary objective of this study is to review trials demonstrating biological activity of cell-based cancer vaccines that could uncover additional hypotheses, which could be used in the design of future studies. We performed the systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The final review included 36 studies - 16 single-arm studies, and 20 controlled trials. Our systematic review of the existing literature revealed largely negative trials and our meta-analysis did not show evidence of clinical benefit from cell-based cancer-vaccines. However, as we looked beyond the stringent inclusion criteria of our systematic review, we identified significant examples of biological activity of cell-based cancer vaccines that are worth highlighting. In conclusion, the existing literature on cell-based cancer vaccines is highly variable in terms of cancer type, vaccine therapies and the clinical setting with no overall statistically significant clinical benefit, but there are individual successes that represent the promise of this approach. As cell-based vaccine technology continues to evolve, future studies can perhaps fulfill the potential that this exciting field of anti-cancer therapy holds.

Outcomes Associated With Intensive Care and Organ Support Among Patients With COVID-19: A Systematic Review and Meta-Analysis

BACKGROUND

Accurate accounting of coronavirus disease 2019 (COVID-19) critical care outcomes has important implications for health care delivery.

RESEARCH QUESTION

We aimed to determine critical care and organ support outcomes of intensive care unit (ICU) COVID-19 patients and whether they varied depending on the completeness of study follow-up or admission time period.

STUDY DESIGN AND METHODS

We conducted a systematic review and meta-analysis of reports describing ICU, mechanical ventilation (MV), renal replacement therapy (RRT), and extracorporeal membrane oxygenation (ECMO) mortality. A search was conducted using PubMed, Embase, and Cochrane databases.We included English language observational studies of COVID-19 patients, reporting ICU admission, MV, and ICU case fatality, published from December 1, 2019 to December 31, 2020. We excluded reports of less than 5 ICU patients and pediatric populations. Study characteristics, patient demographics, and outcomes were extracted from each article. Subgroup meta-analyses were performed based on the admission end date and the completeness of data.

RESULTS

Of 6,778 generated articles, 145 were retained for inclusion (n = 60,357 patients). Case fatality rates across all studies were 34.0% (95% CI = 30.7%, 37.5%, P < 0.001) for ICU deaths, 47.9% (95% CI = 41.6%, 54.2%, P < 0.001) for MV deaths, 58.7% (95% CI = 50.0%, 67.2%, P < 0.001) for RRT deaths, and 43.3% (95% CI = 31.4%, 55.4%, P < 0.001) for extracorporeal membrane oxygenation deaths. There was no statistically significant difference in ICU and organ support outcomes between studies with complete follow-up versus studies without complete follow-up. Case fatality rates for ICU, MV, and RRT deaths were significantly higher in studies with patients admitted before April 31st 2020.

INTERPRETATION

Coronavirus disease 2019 critical care outcomes have significantly improved since the start of the pandemic. Intensive care unit outcomes should be evaluated contextually (study quality, data completeness, and time) for the most accurate reporting and to effectively guide mortality predictions.

DIAGNOSTIC VALUE OF MITOCHONDRIAL DNA AND PERIPHERAL BLOOD MONONUCLEAR CELL RESPIROMETRY FOR BURN-RELATED SEPSIS

ABSTRACT

Background: Sepsis is the leading cause of mortality among burn patients that survive acute resuscitation. Clinical criteria have poor diagnostic value for burn-induced sepsis, making it difficult to diagnose. Protein biomarkers (e.g., procalcitonin) have been examined with limited success. We aimed to explore other biomarkers related to mitochondria (mitochondrial DNA [mtDNA]) and mitochondrial function of peripheral blood mononuclear cells (PBMCs) for sepsis diagnosis in burn patients. Methods: We conducted a follow-up analysis of a single center, prospective observational study of subjects (n = 10 healthy volunteers, n = 24 burn patients) to examine the diagnostic value of mtDNA and PBMC respirometry. Patients were enrolled regardless of sepsis status and followed longitudinally. Patient samples were classified as septic or not based on empiric clinical criteria. Isolated PBMCs were loaded into a high-resolution respirometer, and circulating mtDNA was measured with a PCR-based assay. Sequential Organ Failure Assessment (SOFA) criteria were also compared. Results: The SOFA criteria comparing septic versus before/nonseptic patients revealed significantly higher heart rate ( P = 0.012) and lower mean arterial pressure ( P = 0.039) in burn sepsis. MtDNA was significantly elevated in septic burn patients compared with healthy volunteers ( P < 0.0001) and nonseptic patients ( P < 0.0001), with no significant difference between healthy volunteers and nonseptic burn patients ( P = 0.187). The area under the ROC curve (AUC) for mtDNA was 0.685 (95% confidence interval = 0.50-0.86). For PBMC respirometry, burn patients exhibited increased routine and maximal respiration potential compared with healthy volunteers. However, no difference was found between nonseptic and septic patient samples. A subanalysis revealed a significant mortality difference in PBMC respirometry after sepsis diagnosis, wherein survivors had higher routine respiration ( P = 0.003) and maximal respiration ( P = 0.011) compared with nonsurvivors. Conclusion: Our findings reveal that mtDNA may have diagnostic value for burn sepsis, whereas PBMC respirometry is nonspecifically elevated in burns, but may have value in mortality prognosis. A larger, multisite study is warranted for further validity of the diagnostic value of mtDNA and PBMC respirometry as biomarkers for prognosis of sepsis and outcomes in burn patients.

Suicide attempts and mental health diagnoses in combat-injured service members: A retrospective cohort study

INTRODUCTION

Examinations of risk factors for suicide attempt in United States service members at high risk of mental health diagnoses, such as those with combat injuries, are essential to guiding prevention and intervention efforts.

METHODS

Retrospective cohort study of 8727 combat-injured patients matched to deployed, non-injured patients utilizing Department of Defense and Veterans Affairs administrative records.

RESULTS

Combat injury was positively associated with suicide attempt in the univariate model (HR = 1.75, 95% CI 1.5-2.1), but lost significance after adjustment for mental health diagnoses. Utilizing Latent Transition Analysis in the combat-injured group, we identified five mental/behavioral health profiles: (1) Few mental health diagnoses, (2) PTSD and depressive disorders, (3) Adjustment disorder, (4) Multiple mental health comorbidities, and (5) Multiple mental health comorbidities with alcohol use disorder (AUD). Multiple mental health comorbidities with AUD had the highest suicide attempt rate throughout the study and more than four times that of Multiple mental health comorbidities in the first study year (23.4 vs. 5.1 per 1000 person years, respectively).

CONCLUSION

Findings indicate that (1) combat injury's impact on suicide attempt is attenuated by mental health and (2) AUD with multiple mental health comorbidities confers heightened suicide attempt risk in combat-injured service members.

Social and Professional Impact of Learning Communities Within the Alliances for Graduate Education and the Professoriate Program at Michigan State University

At Michigan State University (MSU), the AGEP learning community features the participation of over 70% of the African-American, Latinx, and Native-American under-represented minorities (URM), also referred to as Black, Indigenous, and People of Color (BIPOC) doctoral students in fields sponsored by the National Science Foundation (NSF). Monthly learning community (LC) meetings allow AGEP participants to create dialogues across disciplines through informal oral presentations about current research. The learning communities also offer opportunities to share key information regarding graduate school success and experience; thus providing a social network that extends beyond the academic setting. At MSU, AGEP also provides an interdisciplinary and multigenerational environment that includes graduate students, faculty members, post-docs and prospective graduate students. Using monthly surveys over a 4-year period, we evaluated the impact of this AGEP initiative focusing on the utility of the program, perceptions of departmental climate, career plans and institutional support. Findings indicate that AGEP participants consider their experiences in the program as vital elements in the development of their professional identity, psychological safety, and career readiness. Experiences that were identified included networking across departments, focus on career placement, involvement in minority recruitment and professional development opportunities. Additionally, AGEP community participants resonated with the "sense of community" that is at the core of the MSU AGEP program legacy. In this article, we proposed a variation of Tomlinson's Graduate Student Capital model to describe the AGEP participants' perceptions and experiences in MSU AGEP. Within this 4-year period, we report over 70% graduation rate (completing with advanced degrees). More than half of Ph.D. students and almost 30% of master's degree students decided to pursue academia as their careers. In addition, we found a high satisfaction rate of AGEP among the participants. Our analysis on graduate student capital helped us identify motivating capital development by years spent at MSU and as an AGEP member. These findings may provide some insight into which capitals may be deemed important for students relative to their experiences at MSU and in AGEP and how their priorities change as they transition toward graduation.

Development and Validation of a Prediction Model of Prescription Tranquilizer Misuse Based on a Nationally Representative United States Sample

BACKGROUND

Prescription tranquilizer misuse is a risky behavior associated with fatal drug poisonings. Although various predictors have been examined, there is no published prediction model for tranquilizer misuse. This study develops and internally validates a tranquilizer misuse prediction model based primarily on drug histories of participants in a national cross-sectional survey. Predictors also include psychiatric, behavioral and demographic variables.

METHODS

We analyzed data from 471,097 individuals aged 14-to-29-years in the United States, as sampled by the National Survey of Drug Use and Health, 2004-2018, an annual cross-sectional survey. We encoded 21 predictors with known or likely onset prior to tranquilizer misuse initiation, (e.g., early onset of cannabis use). With this dataset, we trained a neural network and regularized logistic regression model. While the assessment for tranquilizer misuse changed slightly in 2015, by pooling all years of survey data, predictions are robust to this source of variation.

RESULTS

1.44% of the pooled sample, 2004-2018, recently initiated tranquilizer misuse (unweighted estimate). On held-out test data (n = 43,714), logistic regression and the neural network performed equally well, with an area under the receiver operating characteristic curve (AUC) of ∼0.83 on the primary model, containing 12 variables known to occur before tranquilizer misuse.

CONCLUSION

Built for case prediction rather than case detection, this model restricted predictors to those with known timing prior to initiation of tranquilizer misuse. Yet its performance supersedes commonly accepted criteria for clinical prediction models (AUC > 0.80). Future work should incorporate survey analysis weights into the prediction model to minimize possible bias.