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INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

Objective Rapid eye movement sleep behavior disorder (RBD) is a prodromal synucleinopathy, as >80% will eventually convert to overt synucleinopathy. We performed an in‐depth analysis of the SNCA locus to identify RBD‐specific risk variants. Methods Full sequencing and genotyping of SNCA was performed in isolated/idiopathic RBD (iRBD, n = 1,076), Parkinson disease (PD, n = 1,013), dementia with Lewy bodies (DLB, n = 415), and control subjects (n = 6,155). The iRBD cases were diagnosed with RBD prior to neurodegeneration, although some have since converted. A replication cohort from 23andMe of PD patients with probable RBD (pRBD) was also analyzed (n = 1,782 cases; n = 131,250 controls). Adjusted logistic regression models and meta‐analyses were performed. Effects on conversion rate were analyzed in 432 RBD patients with available data using Kaplan–Meier survival analysis. Results A 5′‐region SNCA variant (rs10005233) was associated with iRBD (odds ratio [OR] = 1.43, p = 1.1E‐08), which was replicated in pRBD. This variant is in linkage disequilibrium (LD) with other 5′ risk variants across the different synucleinopathies. An independent iRBD‐specific suggestive association (rs11732740) was detected at the 3′ of SNCA (OR = 1.32, p = 4.7E‐04, not statistically significant after Bonferroni correction). Homozygous carriers of both iRBD‐specific SNPs were at highly increased risk for iRBD (OR = 5.74, p = 2E‐06). The known top PD‐associated variant (3′ variant rs356182) had an opposite direction of effect in iRBD compared to PD. Interpretation There is a distinct pattern of association at the SNCA locus in RBD as compared to PD, with an opposite direction of effect at the 3′ of SNCA . Several 5′ SNCA variants are associated with iRBD and with pRBD in overt synucleinopathies. ANN NEUROL 2020;87:584–598

Introduction. Acquired severe aplastic anemia (SAA) is a life-threatening disorder characterized by severe progressive pancytopenia and hypocellular bone marrow. The etiology of acquired SAA is not understood but believed to be related to abnormal immune responses to environmental exposures. We conducted a genome-wide association study (GWAS) to identify common germline variants associated with SAA. Methods. We identified 895 patients with SAA who underwent related or unrelated hematopoietic cell transplant (HCT) with clinical data and pre-HCT blood samples available in the Center for International Blood and Marrow Transplant Research (CIBMTR) database and biorepository. Pre-HCT DNA was extracted from blood of patients with SAA and genome-wide genotyping was conducted using the Illumina OmniExpress array. We excluded 93 inherited bone marrow failure cases. The SAA cases were grouped cases into discovery and validation sets based on time of batch sample receipt. Analyses were limited to patients of European ancestry based on principal component analyses to minimize the potential effect of population stratification. Controls were genomically matched and selected from previously scanned cancer-free subjects at the Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, NCI. The final analysis included 534 acquired SAA cases (359 in the discovery set and 175 in the validation set), and 2,455 controls (1,396 in the discovery set, and 1,059 in the validation set). Results. Patients with SAA in this study received HCT between 1989-2015 at a median age of 21 years, 56% were male, and the median time between SAA diagnosis and HCT was 11 months. Strong genome-wide association signals were identified across the human leukocyte antigen (HLA) genes encoded at the major histocompatibility complex (MHC) on chromosome 6p21 (Figure 1). The top SNP was located in the P4 binding pocket of the HLA class II gene HLA-DPB1(rs1042151A>G, p.Met105Val, pooled-odds ratio [OR]=1.75, 95% confidence interval [CI]=1.50-2.03, p=1.94x10-13). The expression of HLA-DP in CD19+ cells from 175 healthy donors was significantly different by rs1042151 A>G genotype (p=2.04x10-6) (Figure 2). A second SNP near HLA-B, rs28367832G>A, also reached genome-wide significance (pooled-OR=1.49, 95% CI=1.22-1.78, p=7.27x10-9). Copy-number variant analysis and next generation sequencing also identified somatic, clonal copy-neutral loss-of-heterozygosity affecting class I HLA genes in 8.6% of the SAA cases and none of the controls. Conclusion. This SAA GWAS identified strong association signals between common germline genetic variants in HLA class I and II genes and SAA. The main SNP is associated with changes in HLA-DP expression suggesting a key role for this locus in SAA etiology. This study adds further evidence to the connection between SAA and immune dysregulation. Disclosures Cerhan: Janssen: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; Celgene: Research Funding. Lee:Incyte: Research Funding; Syndax: Research Funding; Amgen: Research Funding; Novartis: Research Funding; Takeda: Research Funding; Kadmon: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; AstraZeneca: Research Funding.

Introduction: Most patients with newly diagnosed FL treated with rituximab (R) alone or R + chemotherapy will experience prolonged progression-free survival and overall survival (OS), but it remains unclear what factors have the greatest influence on FL-associated and other causes of death in this patient population. We utilized individual patient data from 13 first-line randomized clinical trials from the FLASH database to perform a comprehensive multistate survival analysis to examine and quantify the relationships between clinical characteristics, treatment response, and early, intermediate, and late FL outcomes. Methods: The multistate survival analysis model defined states for "Alive after beginning Induction Treatment (TX)", "Alive after beginning Maintenance TX", "Death due to FL", and "Death from Other Causes" (Figure 1). We used the Aalen-Johansen estimator, a generalization of the Kaplan-Meier estimator, to calculate the likelihood of being in each model state and estimate the course of FL over time. Making no assumptions on the probability distributions and capable of coping with censored observations, the Aalen-Johansen estimator is a convenient and reliable nonparametric estimator for clinical data. Results: Among 7,465 FL patients with median age 56 (range 18-90) years, 49.2% were female; 28.7% Stage I-III, 71.3% Stage IV, and FLIPI was 0-1 (20.0%), 2 (36.8%), ≥ 3 (43.2%). Following initiation of induction treatment, 2-, 5- and 10-year death rates were 1.7%, 3.8%, and 5.8% due to FL, and 0.7%, 2.1%, and 4.8% from other causes (Figure 2). Death rates at 2, 5, and 10 years due to FL and other causes for subgroups based on clinical characteristics and treatment response are shown in Table 1. Notably, patients > 70 years and patients with FLIPI ≥ 3 had worse outcomes and patients achieving CR at 18, 24, and 30 months experienced improved outcomes. Conclusion: This is the largest study using data from randomized trials to quantify the impact of clinical factors on early, intermediate and late mortality by cause of death. We demonstrated that age > 70 years and FLIPI ≥ 3 were linked to increased FL-associated death and response to TX distinguished patients with favorable and poor outcomes. Future analyses should quantify the impact of predictors on the rate/time of FL outcomes in multivariable models. Disclosures Salles: Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. Hoster:Janssen: Research Funding; Roche Pharma AG: Other: Travel Support. Hiddemann:Bayer: Research Funding; Gilead: Consultancy, Honoraria; Vector Therapeutics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria. Herold:Roche: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Gilead: Honoraria; Celgene: Honoraria. Morschhauser:Servier: Consultancy; Gilead: Consultancy; Janssen: Honoraria; Roche/Genentech: Consultancy; BMS: Honoraria; Celgene: Honoraria. Rummel:Roche Pharma AG: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Sandoz: Honoraria. Kimby:AbbVie,: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Gilead: Other: educational lectures. Vitolo:Abbvie: 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; Celgene: 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; Gilead: 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; F. Hoffmann-La Roche: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gyan:Pfizer: Honoraria. Ladetto:Celgene: Honoraria; Roche: Honoraria; Janssen: Honoraria; Abbvie: Honoraria; Acerta: Honoraria; Sandoz: Honoraria. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Flowers:AstraZeneca: Consultancy; BeiGene: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Optimum Rx: Consultancy; V Foundation: Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; Bayer: Consultancy; Gilead: Consultancy, Research Funding; TG Therapeutics: Research Funding; Denovo Biopharma: Consultancy; Acerta: Research Funding; National Cancer Institute: Research Funding; Millenium/Takeda: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Spectrum: Consultancy;

Abstract Background Myelofibrosis (MF), polycythemia vera (PV), and essential thrombocythemia (ET) are myeloproliferative neoplasms (MPNs) whose associated disease burden includes a range of debilitating symptoms, thrombosis, hemorrhage, and shortened survival. To enhance patient care, it is important to understand the impact of MPNs in patients' lives; however, little is known regarding how these conditions affect patients' quality of life (QOL), activities of daily living, productivity, and emotional well-being. The US LANDMARK survey (Mesa et al. BMC Cancer 2016) captured data for US patients. Here, we present an interim analysis of results of another MPN LANDMARK survey conducted in the rest of the world. Methodology MPN LANDMARK survey is a cross-sectional survey of MPN patients across 6 countries (Australia, Canada, Germany, Japan, Italy, and UK). Patients completed an online questionnaire to measure MPN related symptoms experienced over the past 12 months and the impact of their condition on their QOL and ability to work. Additional questions related to employment productivity and activity impairment (including absenteeism and loss of productivity over the past 7 days). Patients included in this interim analysis had completed the survey by July 18, 2016, with enrollment continuing in all countries. Results Patients: Overall, 437 patients had completed the survey (98 MF, 121 PV, 218 ET). For MF and PV, the male to female gender split was relatively even (54% male for each), whereas an expected greater proportion of ET patients was female (70%). Patients with MF were significantly older than PV and ET patients (mean ages, 62, 59, and 55 years, respectively) and more had been diagnosed within 2 years of experiencing their symptoms (83% MF, 67% PV, 71% ET). MPN Symptoms (Table): Most patients (94%) experienced MPN-related symptoms in the past 12 months. The most commonly reported symptom among all subtypes was fatigue (69% MF, 62% PV, 73% ET), incidence of other common symptoms varied depending on disease subtype (MF: shortness of breath [38%], bruising [36%], night sweats [35%], early satiety [33%]; PV: night sweats [36%], trouble concentrating [36%], trouble sleeping [34%], dizziness [34%]; ET: trouble sleeping [37%], dizziness [37%], bruising [35%], night sweats [35%]). When asked which symptom patients would most like to have resolved, most patients preferred to have feeling of fatigue/tiredness improved across all disease subtypes (31% MF, 30% PV, 33% ET). Patients experienced an average of 6.4 symptoms at diagnosis but this progressed to an average of 7.6 symptoms since diagnosis after a median time of 6 years. QOL: A majority of patients indicated that they experienced a reduction in QOL due to MPN symptoms (87% MF, 71% PV, 73% ET) with 33% and 26% of MF and ET patients expressing that their condition has caused emotional hardship, and one-third of patients with PV reporting that they have felt worried or anxious about their disease (39%). MPN Impact on Activity/Employment: Patients reported a high impact on their ability to work, 12% reported voluntarily leaving their job, 10% had taken early retirement, 10% had moved onto disability living allowance, 8% moved to a lower paid job, and 2% experienced involuntary loss of work (Table). Of the patients who were in full-time or part-time employment at the time of the survey (MF [n=17]), PV [n=41], ET [n=98]), approximately, 40% had been absent from work within the past 7 days; this was the highest in MF patients (41% MF, 38% PV, 33% ET). On an average, over the past 7 days, MF patients had missed 3.1 hours from work, PV patients 2.3 hours and ET patients 2 hours. Across all subgroups, a substantial proportion of patients reported impairment in work (mean: 34% MF, 33% PV, 31% ET) and overall activity (mean: 46% MF, 42% PV, 39% ET). Conclusions This interim analysis from the MPN LANDMARK survey indicates that MPN patients experience a high burden of disease, including a high prevalence of symptoms, an increase in the number of symptoms from diagnosis and reduction of their emotional well-being, QOL, and ability to work. These results are consistent with those from the previous US LANDMARK survey with the addition of novel data on how MPNs impact work. When treating MPN patients, care should be taken in trying to manage a patient's disease burden, so as to minimize the impact on a patient's daily life. Further results from additional survey responses will be presented at the congress. Disclosures Harrison: Baxaltra: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Other: travel, accommodations, expenses, Research Funding, Speakers Bureau; Gilead: Honoraria, Speakers Bureau; Incyte Corporation: Honoraria, Speakers Bureau; Shire: Honoraria, Speakers Bureau. Koschmieder:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Foltz:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Koehler:Novartis Inc. (Germany): Consultancy, Other: Training. Komatsu:Shire: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Boothroyd:Novartis: Employment, Equity Ownership. Spierer:Novartis: Employment. Ronco:Novartis: Employment. Taylor-Stokes:Adelphi Real World: Employment. Waller:Adelphi Real World: Employment. Mesa:Celgene: Research Funding; Galena: Consultancy; Novartis: Consultancy; CTI: Research Funding; Ariad: Consultancy; Incyte: Research Funding; Gilead: Research Funding; Promedior: Research Funding.

Abstract Background: Limited data exist to describe the clinical features and outcomes for elderly pts with FL. The FLASH group performed a prospectively planned pooled analysis of IPD from first-line RCTs and examined associations between age (<= 70 vs. > 70 years), clinical characteristics and FL outcomes. Methods: We identified 18 randomized controlled multicenter clinical trials in the FLASH database which enrolled elderly pts (> 70 yrs). From these 18 studies, 5922 previously untreated FL pts were included for this analysis. Complete response (CR) at 24 and 30 months were defined as whether the pt achieved and remains in CR at 24 months and 30 months after initiation of induction treatment. PFS24 is defined as proportion of pts progression-free and alive at 24 months post-randomization. Time to progression (TTP) and overall survival (OS) were defined as time from randomization to the date of progression (censoring for death without progression) and date of death due to any cause, respectively. Progression-free survival (PFS) was defined as time from randomization to the date of progression or death, due to any cause, whichever comes first. Non-lymphoma death was defined as death without prior progression. Early disease outcomes, i.e. CR24, CR30, and PFS24 were primary outcomes; secondary outcomes were TTP, OS, and PFS. For time-to-event outcomes, Kaplan-Meier method and log-rank test were used for univariate estimation and comparison; stratified Cox proportional hazard modeling was used for multivariable analyses. Cumulative incidence methods were used to model PFS while treating disease progression as the primary event of interest and non-lymphoma death as a competing risk. For binary outcomes, multivariable logistic regression was used to estimate the association between age groups and outcomes. Variable adjusted in the regression models are FLIPI score without the age component, ECOG performance status (>= 2 vs < 2), and rituximab use. Results: Among 5922 previously untreated FL pts from 18 RCTs, 63% (n = 3728) were <= 60, 28% (n = 1652) 61-70, and 9% (n = 542) > 70 yrs. Pts age > 70 (vs. <= 70) more commonly had elevated LDH (42% vs 36%, p = 0.02), hemoglobin < 12 g/dL (27% vs 19%, p < 0.0001), ECOG PS >= 2 (8.8% vs 5.0%, p = 0.0004), and elevated β2-microglobulin (68% vs 49%, p < 0.001), less often had > 4 lymph nodes involved (54% vs 65%, p < 0.001), and had similar FLIPI scores without age component (p = 0.17). There were no significant differences between groups in: Ann Arbor stage (94% vs 95% stage III/IV) or rituximab use (62% vs 58%). Median survival follow-up was 5.6 yrs. Pts > 70 yrs did not differ from pts <= 70 in rates of CR24 (27% vs 30%, p=0.32), CR30 (29% vs 31%, p=0.55) or PFS24 (63% vs. 67%, p=0.10). Median TTP was 3.8 and 4.0 years for pts > 70 and <= 70, respectively (HR=1.08, 95% CI 0.96-1.23, p=0.20). With a median OS of 14.6 years for all pts, median OS was 7.4 and 15.7 years for pts > 70 and <= 70, respectively (HR=2.35, 95% CI=2.03-2.73, p<0.001). PFS was statistically significantly different but clinically similar at median 3.1 and 3.8 years for pts > 70 and <= 70, respectively (HR=1.26, 95% CI =1.12-1.41, p<0.001). Further investigation showed the difference in PFS was due to higher incidence of non-lymphoma death in pts > 70 with no difference in disease progression (Figure). In regression models, adjusting for rituximab use, ECOG PS >= 2, and FLIPI score without the age component, age > 70 was a significant predictor of OS and PFS (due to higher incidence of non-lymphoma death), but not PFS24, CR24 or CR30 (Table). Conclusions: FL pts > 70 yrs treated on trials have similar early disease outcomes to younger patients. There is no disease-specific outcome difference between age groups. Age alone should not disqualify patients from standard treatments or RCTs. Disclosures Flowers: Genentech: Consultancy, Research Funding; NIH: Research Funding; Mayo Clinic: Research Funding; TG Therapeutics: Research Funding; Millenium/Takeda: Research Funding; ECOG: Research Funding; Acerta: Research Funding; Pharmacyclics, LLC, an AbbVie Company: Research Funding; Roche: Consultancy, Research Funding; AbbVie: Research Funding; Infinity: Research Funding; Gilead: Consultancy, Research Funding. Ou:Mayo Clinic: Employment. Shi:Mayo Clinic: Employment. Hochster:Genentech: Consultancy, Other: Consultancy fees for advisory boards for GI cancer and bevacizumab with amounts within Yale University de minims guidelines. Brice:Roche: Honoraria; Takeda Pharmaceuticals International Co.: Honoraria, Research Funding; Bristol Myers-Squibb: Honoraria; Gilead: Honoraria; Seattle Genetics: Research Funding. Hiddemann:Roche: Other: Grants; Roche: Membership on an entity's Board of Directors or advisory committees; Genentech: Other: Grants. Marcus:Takeda: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau. Kimby:Abbvie: Consultancy, Honoraria; Jansen: Consultancy, Honoraria; Celgene: Honoraria; Baxalta: Consultancy; Gilead: Honoraria. Herold:Gilead: Other: Personal fees from member advisory board; Celgene: Honoraria; Genentech: Other: Grants; Roche: Honoraria, Other: Grants. De Bedout:Celgene: Employment. Nielsen:Hoffmann-La Roche: Employment. Morschhauser:Roche: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Gilead Sciences: Consultancy, Honoraria; Janssen: Honoraria. Rummel:Mundipharma GmbH: Other: Personal fees, Research Funding; Roche Pharma AG: Other: Personal fees, Research Funding. Vitolo:Gilead: Other: Honoraria for lectures; Takeda: Other: Honoraria for lectures; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Honoraria for lectures; Janssen: Membership on an entity's Board of Directors or advisory committees, Other: Honoraria for lectures. Salles:Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Gilead: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Roche/Genentech: Consultancy, Honoraria, Research Funding; Mundipharma: Honoraria. Sargent:Celgene: Research Funding.

Abstract Background Rituximab in combination with chemotherapy has been shown to improve overall survival (OS) in pts with FL compared with chemotherapy alone. The effect of MR was evaluated in randomized clinical trials (RCTs) with conflicting results regarding OS. In a previous systematic review and meta-analysis of summary (aggregate) data we demonstrated an OS benefit of MR treatment in pts with relapsed or refractory FL and an improved progression free survival (PFS) in both untreated and relapsed refractory FL. However, pts' disease and treatment characteristics may interact with the effect of MR. To improve identification of sub-groups of pts who may benefit from MR treatment, and to evaluate factors that interact with the effect of MR we conducted an international IPD (raw data) meta-analysis of RCTs of MR for pts with FL. We present the first analysis of this meta-database. Methods In June 2014, we updated an electronic search in Pubmed and the Cochrane Library, conference proceedings and database of clinical trials for randomized trials comparing MR to observation. The investigators of eleven trials that fulfilled inclusion criteria were invited to cooperate. Results of one trial were not reported and this trial could not be included in the meta-analysis. Seven study groups participated in this collaborative project and contributed data on individual pts, including disease characteristics, past treatment, response, survival and adverse events. We examined the effect of pt, disease and treatment characteristics by performing a series of Cox regression analyses stratified by trial. In a sensitivity analysis we combined the assessed log hazard ratios (HR) using a log-rank test for each study and combined the results using a fixed effect meta-analysis. Results We obtained data for 2323 patients randomized in 7 trials of MR compared to observation after induction therapy. The median follow up ranged from 28-114 months. The median age was 57 years (23 - 85 years), and 41% were older than 60 years. 50% of pts were women, 97% had WHO performance status 0-1; 1195 (53%) pts received CHOP/RCHOP, 453 (20%) CVP/R CVP; 1755 (77%) received rituximab containing induction; 33% of pts received 1st induction, 67% ≥2nd. Overall, pts less than 60 years of age (vs. ≥60 years) (p < 0.0001), and women (p = 0.001) had a better prognosis. There was no interaction between sex and the effect of MR (p = 0.65). Pts treated with MR had an improved OS compared to observation (HR 0.76, 95% CI 0.62-0.93, p=0.008, Figure). This was demonstrated also in a sensitivity analysis of 10 studies fulfilling inclusion criteria. There was no statistically significant heterogeneity of treatment effect between trials (p=0.15). In an analysis by treatment line (1st vs. ≥2nd), the estimated effect of MR among patients who received ≥2nd induction was HR of 0.70 (95% CI 0.55 - 0.91), compared to 0.90 (95% CI 0.65 - 1.25) among patients who received 1st induction. However, this difference was not statistically significant (p=0.25). Analysis by the inclusion of rituximab in induction demonstrated among patients who received rituximab in induction a HR of 0.82 (95% CI 0.63 – 1.06), and among those who received induction without rituximab a HR of 0.68 (95% CI 0.49 – 0.93). This difference was not statistically significant (p= 0.35). Analysis by chemotherapy regimen demonstrated an estimated effect for MR among patients who received RCHOP/CHOP of 0.79, 95% CI 0.58 – 1.06, and after RCVP/CVP of 0.65, 95% CI 0.42 – 1.02, with no statistically significant difference between these sub-groups (p = 0.50). Conclusions This is the first report of the collaborative group of maintenance therapy for FL patients. Based on individual patient data, this study demonstrated an improved OS with MR therapy for patients with FL. A sensitivity analysis with all 10 eligible trials supported these results. Results support the effectiveness of MR among patients after their 1st induction as well as after ≥2nd induction, and irrespective of inclusion of rituximab in induction, and the chemotherapy regimen. These results are consistent with those of the summary data meta-analysis that was previously published. The wider CI and lack of statistical significance within sub-groups could be attributed to the sample size. Figure: Pooled HR of death of MR compared to observation in patients with follicular lymphoma. In one study there were no events in one group and it is not represented in the forest plot. Figure:. Pooled HR of death of MR compared to observation in patients with follicular lymphoma. In one study there were no events in one group and it is not represented in the forest plot. Disclosures Vidal: Roche: unrestricted grant Other. Shpilberg:Roche: Consultancy, Research Funding.