Citations

Abstract Aim To appraise the current evidence on the efficacy and safety of lamotrigine (LAM) in the treatment of pediatric mood disorders (PMD) (i.e., Major Depressive disorder [MDD], bipolar disorder [BD]). Methods Major databases were searched for randomized controlled trials (RCTs), open‐label trials, and observational studies reporting on pediatric (age < 18 years) patients treated with LAM for mood disorders. Results A total of 3061 abstracts were screened and seven articles were selected for inclusion. Seven studies (319 BD and 43 MDD patients), including one RCT ( n = 173), three prospective ( n = 105), and three retrospective ( n = 84) studies, met the study criteria with a study duration range from 8 to 60.9 weeks. The mean age of this pooled data is 14.6 ± 2.0 years. LAM daily dosage varied from 12.5 to 391.3 mg/day among the studies. In an important finding, the RCT reported favorable outcomes with LAM (HR = 0.46; p = 0.02) in 13‐ to 17‐year‐old age group as compared with 10‐ to 12‐year‐old age group (HR = 0.93; p = 0.88). In addition, time to occurrence of a bipolar event trended toward favoring LAM over placebo. All the studies identified LAM as an effective and safe drug in PMDs especially, BDs. Overall, LAM was well tolerated with no major significant side effects and no cases of Stevens–Johnson syndrome. Conclusions Most studies suggested that LAM was safe and effective in pediatric patients with mood disorders. However, the data regarding the therapeutic range for LAM are lacking. Based on the data, there is inconsistent evidence to make conclusive recommendations on therapeutic LAM dosage for mood improvement in the pediatric population. Further studies including larger sample sizes are required to address this relevant clinical question.

Summary Anaemia is a common sequela of surgery, although its relationship with patient recovery is unclear. The goal of this investigation was to assess the associations between haemoglobin concentrations at the time of hospital discharge following major surgery and early post‐hospitalisation outcomes, with a primary outcome of 30 day unanticipated hospital readmissions. This investigation includes data from two independent population‐based observational cohorts of adult surgical patients (aged ≥ 18 years) requiring postoperative intensive care unit admission between 1 January 2010 and 31 December 2019 in hospitals in Olmsted County, Minnesota, and between 1 July 2010 and 30 June 2017 in the Kaiser Permanente Northern California integrated healthcare system, California. Cox proportional hazards models assessed the associations between discharge haemoglobin concentrations (per 10 g.l –1 ) and outcomes, with prespecified multivariable adjustment. A total of 3260 patients were included from Olmsted County hospitals and 29,452 from Kaiser Permanente Northern California. In adjusted analyses, each 10 g.l –1 decrease in haemoglobin at hospital discharge was associated with a 9% (hazard ratio 1.09, 95%CI 1.02–1.18; p = 0.014) and 8% increase (hazard ratio 1.08, 95%CI 1.06–1.11; p < 0.001) in the hazard for readmission within 30 days in Olmsted County and Kaiser Permanente Northern California, respectively. In a sensitivity analysis exploring relationships across varying levels of pre‐operative anaemia severity, these associations remained consistent, with lower discharge haemoglobin concentrations associated with higher readmissions irrespective of pre‐operative anaemia severity. Anaemia at hospital discharge in surgical patients requiring postoperative intensive care is associated with increased rates of hospital readmission in two large independent cohorts. Future studies are necessary to evaluate strategies to prevent and/or treat anaemia in these patients for the improvement of post‐hospitalisation outcomes.

Introduction: The Clinical Global Impressions-Improvement (CGI-I) scale is widely used in clinical research to assess symptoms and functioning in the context of treatment. The correlates of the CGI-I with efficacy scales for adolescent major depressive disorder are poorly understood. This study focused on benchmarking CGI-I scores with changes in the Children's Depression Rating Scale-Revised (CDRS-R) and the Quick Inventory of Depressive Symptomatology-Adolescent (17-item) Self-Report (QIDS-A17-SR). Methods: We examined three datasets with the clinician-rated CDRS-R to ascertain equivalent percent changes in total scores and CGI-I ratings. Exploratory analyses examined corresponding percentage changes in the QIDS-A17-SR and the CGI-I ratings. The CGI-I was the reference scale for nonparametric equipercentile linking with the Equate package in R. Results: CGI-I scores of 1 mapped to ≥78%–95% change in CDRS-R scores at 4–6 weeks across three datasets. CGI-I scores of 2 mapped to 56%–94% change in CDRS-R scores at 4–6 weeks across three studies. CGI-I scores of 3 mapped to 30%–68% changes in CDRS-R scores at 4–6 weeks across three studies. CGI-I scores of 4 mapped to a range of 29%–44% at 4–6 weeks across three studies. There was no significant difference ( p ≥ 0.6) between treatment groups in both the Treatment of Adolescents with Depression and Treatment of Resistant Depression in Adolescents studies, for each CGI-I score ( = 1, or = 2 or = 3, or ≥4), associated mapping of total depression severity score, or associated percent change from baseline for corresponding follow-up visits. There was no significant sex difference ( p > 0.2) in CGI-I linkages to CDRS-R total or percentage changes. Conclusions: These findings establish clear relationships among CGI-I scores and the CDRS-R and the QIDS-A17-SR. These benchmarks have utility for clinical trial study design, inter-rater reliability training, and clinical implementation.

Background/Objective: The aim of this study was to determine if plasma concentrations of 5 surrogate markers of Alzheimer’s disease (AD) pathology and neuroinflammation are associated with disease status in African Americans. Methods: We evaluated 321 African Americans (159 AD, 162 controls) from the Florida Consortium for African-American Alzheimer’s Disease Studies (FCA3DS). Five plasma proteins reflecting AD neuropathology or inflammation (Aβ42, tau, IL6, IL10, TNFα) were tested for associations with AD, age, sex, APOE and MAPT genotypes, and for pairwise correlations. Results: Plasma tau levels were higher in AD when adjusted for biological and technical covariates. APOE ɛ4 was associated with lower plasma Aβ42 and tau levels. Older age was associated with higher plasma Aβ42, tau, and TNFα. Females had lower IL10 levels. Inflammatory proteins had strong pairwise correlations amongst themselves and with Aβ42. Conclusion: We identified effects of demographic and genetic variants on five potential plasma biomarkers in African Americans. Plasma inflammatory biomarkers and Aβ42 may reflect correlated pathologies and elevated plasma tau may be a biomarker of AD in this population.

Suicide is a major public health concern; nevertheless, its neurobiology remains unknown. An area of interest in suicide research is the dorsolateral prefrontal cortex (DLPFC). We aimed to identify altered proteins and potential biological pathways in the DLPFC of individuals who died by suicide employing mass spectrometry-based untargeted proteomics. Postmortem DLPFC from age-matched male suicide mood disorder cases (n = 5) and non-suicide mood disorder cases (n = 5) were compared. The proteins that differed between groups at false discovery rate (FDR) adjusted p-values (Benjamini–Hochberg–Yekutieli) <0.3 and Log2 fold change (FC) >|0.4| were considered statistically significant and were subjected to pathway analysis by Qiagen Ingenuity software. Thirty-three of the 5162 detected proteins showed significantly altered expression levels in the suicide cases and two of them after adjustment for body mass index. The top differentially expressed protein was potassium voltage-gated channel subfamily Q member 3 (KCNQ3) (Log2FC = −0.481, p = 2.10 × 10−09, FDR = 5.93 × 10−06), which also showed a trend to downregulation in Western blot (p = 0.045, Bonferroni adjusted p = 0.090). The most notably enriched pathway was the GABA receptor signaling pathway (p < 0.001). Here, we report a reduction trend of KCNQ3 levels in the DLPFC of male suicide victims with mood disorders. Further studies with a larger sample size and equal sex representation are needed.

Introduction: The use of PET-CR as a surrogate endpoint would expedite the development of novel therapies and enable better estimates of sample size based on early outcomes of a trial. Previous studies have reported an association between end-of-therapy (EOT) PET results and long-term progression-free (PFS) and overall survival (OS) in diffuse large B-cell lymphoma (DLBCL) patients receiving standard first-line chemoimmunotherapy. We have also previously shown that the overall predictability of PET-CR for PFS and OS in these trials is similar to that in 18 literature-based studies. (15-ICML 2019, P195). To assess the potential for PET-CR as a surrogate endpoint in registration trials, we conducted a prospectively designed individual patient-level-data meta-analysis of available clinical trials. Methods: We synthesized patient-level data from three prospective phase II and III trials (GOYA [NCT01287741], GATHER [NCT01414855], MAYO [NCT00670358]) conducted in previously untreated DLBCL patients, using a Bayesian hierarchical model. We considered the two treatment arms in GOYA (GOYA-R-CHOP [rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone] and GOYA-G-CHOP [obinutuzumab, cyclophosphamide, doxorubicin, vincristine, and prednisone]) separate; hence a total of four arms, excluding patients without baseline PET scans. We investigated the relationship between PET-CR and long-term survival outcomes overall and within patient subgroups. We used Kaplan-Meier plots to compare survival endpoints by PET-CR status. We considered hypothetical RCTs that have PET-CR and PFS as endpoints to show how our model of the relationship between PET-CR and PFS can be used to predict the trial outcome. Results: We included 1496 patients (GOYA-R, GOYA-G, GATHER, MAYO, respectively: 665, 669, 100, 62). EOT PET-CR status was determined by the Lugano criteria in GOYA and by IHP in the other two studies. The overall rate of PET-CR was 72%; respectively 72%, 73%, 62% and 74% per arm. Panel A of the Figure shows Kaplan-Meier plots of PFS by PET-CR status. The Bayesian modeled hazard ratio (HR) comparing PET-CR versus nonCR was 0.13 (95% CI: 0.10, 0.15). The model can be used in planning a clinical trial as follows. Suppose a new therapy improves the PET-CR rate from 70% to 85%. Based on our model the expected HR for PFS treatment effect would be 0.71 (95% CI: 0.58, 0.84). The trial sample size required to demonstrate such an improvement with 90% power is about 650 patients, assuming an accrual rate of 50 patients per month and a minimum follow-up time of 12 months. Panel B of the Figure shows the model-based PFS HR and its CI (shaded) as it depends on the PET-CR rate of the new therapy. This plot also shows the estimated total trial sample size (in red), again assuming the relationship between PET-CR and PFS in our model. However, our model may not apply for the new therapy; and the trial could have an adaptive design with final sample size tailored to the accruing information about PET-CR and PFS and their relationship for the therapies in the trial. Conclusions: Achieving an EOT PET-CR in newly diagnosed DLBCL is highly predictive of favorable outcome in the populations we considered. The estimated HR is 0.13 for PFS, PET-CR versus nonCR, and it is 0.10 for OS. Based on our model, a treatment that improves PET-CR rate could be reasonably expected to have a benefit on PFS and OS, for the populations we considered. Whether a new therapy, with a different mechanism of action, that improves PET-CR rate will extend PFS in a clinical trial is less clear. An adaptive trial could be initiated based on our model as a hypothesis. This hypothesis can be verified or updated using accruing information in the trial itself. Our model can also help in planning clinical trials for re-estimating sample size during the trial and considering early stopping for futility. Further work should investigate the applicability of PET-CR in predicting PFS and/or OS for treatments that have different mechanisms of action and for other populations of patients. Acknowledgements: This work was funded by Genentech/Roche. Disclosures Berry: Berry Consultants, LLC: Consultancy, Employment, Equity Ownership, Other: Berry Consultants, LLC is a company that provides statistical design and analysis services to pharmaceutical companies (including Genentech/Roche), medical device companies, U.S. NIH cooperative groups, patient advocacy groups, and international consortia. Broglio:Berry Consultants LLC: Employment. Ward:Hoffmann La Roche: Employment, Equity Ownership. Mattiello:F. Hoffmann-La Roche Ltd: Employment. Sahin:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. McGlothlin:Berry Consultants, LLC: Consultancy, Employment. Elliott:Berry Consultants, LLC: Employment. Sehn:Lundbeck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Janssen-Ortho: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Merck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Astra Zeneca: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Verastem: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Janssen-Ortho: Honoraria; Takeda: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria. Trněný:Abbvie: Consultancy, Honoraria; Gilead Sciences: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Celgene: Consultancy; Janssen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; F. Hoffmann-La Roche: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria. Vitolo:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; F. Hoffmann-La Roche: Speakers Bureau. Martelli:Servier: Honoraria; F. Hoffman-La Roche, Celgene, Janssen, Sandoz, Novartis, Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria; F. Hoffman-La Roche, Celgene, Janssen, Sandoz, Novartis, Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kostakoglu:F. Hoffman-La Roche: Consultancy; Genentech: Consultancy. Nowakowski:F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding.

Abstract Introduction: DLBCL is an aggressive mature B-cell neoplasm with a low incidence in African Americans and other minority groups. The differences in outcomes based on DLBCL Cell of Origin(COO) immunophenotypic subtypes as defined by the Hans algorithm using CD10, Bcl-6, and MUM1 namely germinal center B-cell (GCB) and non-GCB have been based on predominantly Caucasian patients (pts) and their impact on outcomes in AA patients have not been well studied. Material and Methods: A retrospective review of clinicopathologic data from patients diagnosed and treated for DLBCL at UAB between 2002-2011 was conducted following IRB approval .The data collected included patient demographics (age, sex, self identified race), DLBCL subtype (GCB vs. non-GCB based on the Hans algorithm), disease stage, first line therapy regimens and patient outcomes. We analyzed group differences in both C and AA pts with GCB and non-GCB subtypes of DLBCL in all the parameters mentioned above using the chi square test for categorical variables,. In addition, OS was examined using Kaplan Meier curves and the log rank test. We performed univariate and multivariate analyses to examine the effects of variables of interest on OS. All results were considered statistically significant at α=0.05 level. Results: We included a total of 259 pts in our analysis after excluding patients with missing demographics, disease related data, primary mediastianal DLBCL, missing first line therapy data and outcomes data as well as race identified as other than C or AA. 45 patients (17.4%) of patients self identified as AA and 214 (82.6%) self identified as Caucasian. The mean age of presentation for AA pts was 52 yrs compared to 58 years for C patients (p=0.045) and 28 (62.2%) AA patients presented with advanced Stage III and IV disease compared to 89 (44.6%) of C patients (P=0.04) both being statistically significant. Based on COO characterization using immunophenotype by Hans algorithm, 27 AA pts (60%) and 145(67%) of C pts were GCB by immunophenotype(p=0.317). 95% of all patients received R-CHOP as first line therapy , 3.5% received R-CVP and the remaining received a combination of Rituximab alone, FCR or radiation therapy .On analyzing OS based on COO, AA patients did not demonstrate a significant difference in OS based on COO with both GCB and non-GCB groups having a median OS of 84 months ( p=0.74)( 95% CI 72-121 months). However, the median OS for C pts with GCB phenotype was 104 months compared to 25 months for the non-GCB phenotype and the median OS was 55 months +/-12.6 months for the C pt group as a whole( p<0.001 by log rank test )which was highly statistically significant.Multivariate analyses of different factors affecting OS showed only COO (p<0.001), age(p=0.07) and stage of DLBCL at presentation(p=0.027) to affect OS significantly.Race,Gender and IPI score did not appear to impact OS significantly. Conclusion: Our study aimed to study the impact of COO and Race on OS in DLBCL especially in AA pts where this has not been well characterized. Our results show that as expected the incidence of DLBCL is lower in AA patients compared to C pts. However, DLBCL presents at younger age and with more advanced stage in AA than in C patients. Although distribution of COO is similar in AA and C patients, our findings suggest that COO may not have the same effect on prognosis among AA pts as it does among the C pt population where we see non-GCB patients do significantly worse than their GCB counterparts. This may reflect a different disease biology in AA patients that has yet to be understood. Our study limitations include not taking into account disease relapse, second line therapy and effect of autologous bone marrow transplantation on overall survival. Figure 1. Figure 1. Figure 2. Figure 2. Figure 3. Figure 3. Disclosures No relevant conflicts of interest to declare.