Citations

AbstractFebrile infection‐related epilepsy syndrome (FIRES) is a rare catastrophic epileptic encephalopathy that presents suddenly in otherwise normal children and young adults causing significant neurological disability, chronic epilepsy, and high rates of mortality. To suggest a therapy protocol to improve outcome of FIRES, workshops were held in conjunction with American Epilepsy Society annual meeting between 2017 and 2019. An international group of pediatric epileptologists, pediatric neurointensivists, rheumatologists and basic scientists with interest and expertise in FIRES convened to propose an algorithm for a standardized approach to the diagnosis and treatment of FIRES. The broad differential for refractory status epilepticus (RSE) should include FIRES, to allow empiric therapies to be started early in the clinical course. FIRES should be considered in all previously healthy patients older than two years of age who present with explosive onset of seizures rapidly progressing to RSE, following a febrile illness in the preceding two weeks. Once FIRES is suspected, early administrations of ketogenic diet and anakinra (the IL‐1 receptor antagonist that blocks biologic activity of IL‐1β) are recommended.

Background: With the incorporation of positron emission tomography (PET) imaging as part of the standard staging evaluation of follicular lymphoma (FL), it is generally recommended to obtain the diagnostic biopsy from a lesion with the highest standardized uptake value (SUV) to rule out de novo histologic transformation (HT). In some cases such an approach might be impractical, while in other cases a biopsy from a diseased area with a high SUV may still demonstrate an indolent histology. To date, there is no data to guide treatment choices in patients (pts) with FL with high SUVmax but with no documented evidence of HT. Specifically, it remains unclear whether anthracycline-containing regimens, such as R-CHOP, provide a better outcome than R-Bendamustine (BR). Furthermore, it is unknown whether rituximab (R) maintenance is beneficial in this setting. Therefore, we aimed to compare the efficacy of R-CHOP vs BR in newly diagnosed FL pts with high SUVmax at baseline PET and to clarify the role of maintenance. Patients and Methods: We retrospectively identified 261 consecutive pts with newly diagnosed biopsy-proven FL1-3A and a SUVmax≥13 on baseline PET, who were treated with frontline R-CHOP (n=183) or BR (n=78) at 7 US cancer centers based on the physician's choice. Progression-free survival (PFS) was calculated from starting treatment until progression, relapse or death. Cut-offs of SUVmax ≥13≤18 and SUVmax>18 were used for sub-analysis (Haematologica;2020;105:1907-1913). Results: Median age was 59 years. The baseline characteristics of the two groups differed significantly for a younger age (58 vs 62 years, p=0.009), a higher rate of B-symptoms (26% vs 10%, p=0.005) and baseline SUVmax>18 (49% vs 36%, p=0.04) in the R-CHOP group. A diagnostic biopsy was obtained from the site at the highest SUV in 129 (71%) and 43 (55%) pts, respectively (p=0.01). These suggest a potential selection of R-CHOP in pts with adverse features. At the end of therapy (EoT), R-CHOP treated pts achieved higher PET-CT complete response rates (CR 82% vs 69%, p=0.02). This superiority held in pts with diagnostic biopsy at the highest SUV site (CR 83% vs 67%, p=0.03), but not in the others (CR 80% vs 71%, p=0.37). Progression occurred at EoT in 11 and 14 pts receiving R-CHOP and BR (6% vs 18%, p=0.02), with a higher rate of HT in the BR group (13% vs 4%, p=0.006). After a median follow-up of 76 months (range, 4-208 months), there was no significant difference in PFS between R-CHOP and BR treated pts (hazard ratio [HR] 1.22, p=0.34). PFS was strongly associated with FLIPI 2 (HR 2.32, p=0.01) and 3-5 (HR 2.69, p=0.003) in the univariate as well as in the multivariate analysis (FLIPI 2 HR 2.19, p=0.02; FLIPI 3-5 HR 2.51, p=0.01). There was a trend toward overall survival (OS) benefit in the R-CHOP group (Fig.1A). In the univariate analysis for OS, BR regimen (HR 2.12, p=0.03), age >60 (HR 2.54, p=0.006), FLIPI 3-5 (HR 5.13, p=0.03) and biopsy at the highest SUV site (HR 0.44, p=0.01) were prognostic, however none of those remained significant in the multivariate analysis (BR regimen HR 1.84, p=0.09; age >60 HR 1.92, p=0.08; FLIPI 3-5 HR 3.11, p=0.14; biopsy at the highest SUV site HR 0.60, p=0.13; SUVmax>18 HR 1.87, p=0.055). Among pts with EoT response after R-CHOP or BR (n=170 and n=64, respectively), one third in each group (36% vs 41%, respectively) received R-maintenance for a median of 8 administrations (range, 2-12). A significant PFS advantage (landmark analysis) was observed with R-maintenance (Fig.1B; HR 0.53, p=0.02); however, this did not translate in survival benefit (HR 0.67, p=0.49). In a multivariable model, R-maintenance (HR 0.53, p=0.02), FLIPI 2 (HR 2.47, p=0.03) and 3-5 (HR 2.79, p=0.01) remained independent prognosticators of PFS, while no parameters significantly affected OS. The 2-year HT rate (10% vs 17%) and cumulative incidence did not statistically differ between R-CHOP and BR groups (Fig.1C, p=0.159). Early progression (POD24) occurred in 43 and 22 pts who received R-CHOP and BR, respectively (24% vs 28%) and resulted in a significantly higher risk of death (HR 4.12, p=0.006). Conclusion: In newly diagnosed FL pts with SUVmax≥13 at baseline PET, R-CHOP was more effective in achieving CR and reducing the risk of early HT compared with BR, and it was associated with a trend toward survival advantage. Rituximab maintenance significantly prolonged PFS. A prospective evaluation with a larger population will be needed to confirm our findings. Disclosures Joffe: Epizyme: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees. Ruella:Abclon, BMS, NanoString: Consultancy; Abclon: Consultancy, Research Funding; UPenn/Novartis: Patents & Royalties. Svoboda:Adaptive: Consultancy; Astra-Zeneca: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Imbrium: Consultancy; Incyte: Research Funding; Pharmacyclics: Consultancy, Research Funding; Merck: Research Funding; Seattle Genetics: Consultancy, Research Funding; TG: Research Funding; Genmab: Consultancy; Atara: Consultancy. Witzig:Immune Design: Research Funding; Spectrum: Consultancy; Karyopharm Therapeutics: Research Funding; Acerta: Research Funding; Celgene: Consultancy, Research Funding; AbbVie: Consultancy; MorphSys: Consultancy; Incyte: Consultancy. Smith:TG Therapeutics: Consultancy, Research Funding; Janssen: Consultancy; BMS: Consultancy; Celgene: Consultancy, Research Funding; Pharmacyclics: Research Funding; Karyopharm: Consultancy, Research Funding; FortySeven: Research Funding; Acerta: Research Funding; Genentech/Roche: Consultancy, Other: Support of parent study and funding of editorial support, Research Funding. Armand:Affimed: Consultancy, Research Funding; Otsuka: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; IGM: Research Funding; Infinity: Consultancy; Genentech: Research Funding; Sigma Tau: Research Funding; Celgene: Consultancy; Adaptive: Consultancy, Research Funding; Tensha: Research Funding; Roche: Research Funding; Merck & Co., Inc.: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy; ADC Therapeutics: Consultancy. Nastoupil:Janssen: Honoraria, Research Funding; LAM Therapeutics: Research Funding; Gilead/KITE: Honoraria; Gamida Cell: Honoraria; TG Therapeutics: Honoraria, Research Funding; Merck: Research Funding; Novartis: Honoraria, Research Funding; Genentech, Inc.: Honoraria, Research Funding; Karus Therapeutics: Research Funding; Bayer: Honoraria; Celgene: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding. Ansell:Takeda: Research Funding; Regeneron: Research Funding; Bristol Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; AI Therapeutics: Research Funding; ADC Therapeutics: Research Funding. Zelenetz:Novartis: Consultancy; Adaptive Biotechnology: Consultancy; Genentech/Roche: Consultancy; Gilead: Consultancy; Gilead: Research Funding; Celgene: Consultancy; Roche: Research Funding; Amgen: Consultancy; BeiGene: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Sandoz: Research Funding; Celgene: Research Funding; MorphoSys: Research Funding; MEI Pharma: Research Funding. Younes:BioPath, Xynomic, Epizyme, and F. Hoffmann-La Roche: Consultancy; Janssen, Curis, Merck, Bristol-Myers Squibb, Syndax Pharmaceuticals, F. Hoffmann-La Roche, Curis (Inst), Johnson & Johnson (Inst), Novartis (Inst): Research Funding; Janssen, AbbVie, Merck, Curis, Epizyme, F. Hoffmann-La Roche, Takeda, Bristol-Myers Squibb, Bayer HealthCare Pharmaceuticals, Celgene, Incyte, Janssen Pharmaceuticals, Merck, Sanofi, Seattle Genetics, Takeda Millennium: Honoraria; AstraZeneca: Current Employment; MSKCC: Ended employment in the past 24 months.

Background : The presence of TP53 aberrations (defined as del(17p) or TP53 gene mutation) is a strong negative predictor of survival in patients (pts) with CLL. First-line chemoimmunotherapy is suboptimal in pts with CLL bearing TP53 aberrations, with 3-year progression-free survival (PFS) and overall survival (OS) rates of only 18% and 38%, respectively, with fludarabine, cyclophosphamide, and rituximab (Hallek, Lancet 2010). Ibrutinib is the only once-daily Bruton's tyrosine kinase (BTK) inhibitor with significant PFS and OS benefit demonstrated in multiple randomized phase 3 studies (eg, RESONATE-2, ECOG1912) in the first-line treatment of CLL/small lymphocytic lymphoma (SLL). Previous reports of single-agent ibrutinib or ibrutinib-based combination treatments have further demonstrated favorable PFS benefit in pts with TP53 aberrations in both the first-line and relapsed/refractory settings. Despite these study-specific subgroup analyses, there are limited data on long-term outcomes in pts with TP53 aberrations treated with first-line BTK inhibitors. We performed a pooled analysis of data across 4 studies to evaluate the long-term efficacy and safety of first-line ibrutinib-based therapy in pts with CLL bearing TP53 aberrations. Methods : Data for first-line ibrutinib treatment in pts with TP53 aberrations were pooled across 4 clinical trials in CLL/SLL: PCYC-1122e (NCT01500733; single-agent ibrutinib; n=34), PCYC-1130 (NCT02264574; ibrutinib + obinutuzumab; n=18), ECOG1912 (NCT02048813; ibrutinib + rituximab; n=26), and RESONATE-2 (NCT01722487; single-agent ibrutinib; n=11). ECOG1912 and RESONATE-2 excluded pts with del(17p) but did not exclude pts with TP53 mutations. Long-term PFS (assessed by investigator), OS, and safety are reported. Results : Eighty-nine pts with TP53 aberrations receiving first-line ibrutinib treatment were included in this pooled analysis. Median age was 65 years (range 33-87), and 69% of pts were male. At baseline, 53% had Rai stage III/IV, 38% had bulky disease (lymph nodes ≥5 cm), and 69% (of 87 evaluable) had unmutated IGHV. All patients had either del(17p) or TP53 mutation; 53% (of 89 evaluable) had del(17p) and 91% (of 58 evaluable) had TP53 mutation. Among 16 pts with del(17p) who had TP53 sequencing results available, 11 (69%) had both del(17p) and TP53 mutation. Forty-five pts received ibrutinib as a single agent and 44 received ibrutinib in combination with an anti-CD20 agent. With a median follow-up of 50 months (range 0.1 to 95.9 months), median PFS was not reached (95% CI: 67 months to not estimable; Figure 1A). At 48 months, the PFS rate was 79% and the OS rate was 88% (Figure 1B). Median duration of ibrutinib treatment was 46 months (range 0.1 to 95.5 months). Reasons for treatment discontinuation were progressive disease (20%), study closure (12%), adverse event (10%), withdrawal by pt (7%), death (3%), and other (physician decision due to scheduled pt surgery; 1%). Grade ≥3 adverse events of clinical interest with up to 8 years of treatment with ibrutinib were infection (22%; most commonly pneumonia in 7%), hypertension (13%), atrial fibrillation (12%), and major hemorrhage (7%). With the current follow-up, 46% of pts with TP53 aberrations remained on ibrutinib treatment. Conclusions : With a median follow-up of 4 years, first-line ibrutinib-based treatment resulted in sustained efficacy with high PFS and OS rates in CLL pts with TP53 aberrations, a population with historically poor outcomes. Although pts with TP53 aberrations remain at risk for progression, first-line treatment with ibrutinib has partially overcome the poor prognosis in this high-risk population with 4-year PFS and OS rates of 79% and 88%, respectively. No new safety signals were identified in this analysis. These results from a large, pooled, multi-study dataset demonstrated the long-term benefit of first-line ibrutinib-based treatment in pts with TP53 aberrations. Disclosures Allan: Janssen, AbbVie, and AstraZeneca: Other: Travel/accommodations/expenses; Celgene, Genentech, AstraZeneca, TG Therapeutics, and Janssen: Research Funding; AstraZeneca, Pharmacyclics LLC, an AbbVie Company, Genentech, AbbVie, Ascentage, and Cellectar: Consultancy; Janssen, AstraZeneca, and AbbVie: Honoraria. Shanafelt:Genentech, Pharmacyclics LLC, an AbbVie Company, AbbVie, GlaxoSmithKline, and Merck: Research Funding; Mayo Clinic: Patents & Royalties: and other intellectual property. Wiestner:Pharmacyclics LLC, an AbbVie Company; Acerta, Merck, Nurix, Verastem, and Genmab: Research Funding; National Institutes of Health: Patents & Royalties: and other intellectual property. Moreno:Janssen, AbbVie, Sunesis, and AstraZeneca: Consultancy; AbbVie and Janssen: Research Funding; Janssen: Speakers Bureau. O'Brien:Eisai: Consultancy; Juno Therapeutics: Consultancy; Aptose Biosciences: Consultancy; GlaxoSmithKline: Consultancy; Sunesis: Research Funding; Acerta: Research Funding; Amgen: Consultancy; Celgene: Consultancy; Pfizer: Research Funding; Pharmacyclics: Research Funding; Astellas: Consultancy; Gilead: Consultancy; TG Therapeutics: Research Funding; Vida Ventures: Consultancy; KITE: Research Funding; Vaniam Group LL: Consultancy; Alexion: Consultancy; Regeneron: Research Funding; AbbVie: Consultancy; Verastem: Consultancy; Janssen Oncology: Consultancy. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Liu:AbbVie: Current equity holder in publicly-traded company; Pharmacyclics LLC, an AbbVie Company: Current Employment. Dean:AbbVie: Current equity holder in publicly-traded company; Pharmacyclics LLC, an AbbVie Company: Current Employment. Lai:Pharmacyclics LLC, an AbbVie Company: Current Employment; AbbVie and Bristol-Myers Squibb: Current equity holder in publicly-traded company; AbbVie: Other: Travel/accommodations/expenses.

INTRODUCTION: Readmission and death in cirrhosis are common, expensive, and difficult to predict. Our aim was to evaluate the abilities of multiple artificial intelligence (AI) techniques to predict clinical outcomes based on variables collected at admission, during hospitalization, and at discharge. METHODS: We used the multicenter North American Consortium for the Study of End-Stage Liver Disease (NACSELD) cohort of cirrhotic inpatients who are followed up through 90-days postdischarge for readmission and death. We used statistical methods to select variables that are significant for readmission and death and trained 3 AI models, including logistic regression (LR), kernel support vector machine (SVM), and random forest classifiers (RFC), to predict readmission and death. We used the area under the receiver operating characteristic curve (AUC) from 10-fold crossvalidation for evaluation to compare sexes. Data were compared with model for end-stage liver disease (MELD) at discharge. RESULTS: We included 2,170 patients (57 ± 11 years, MELD 18 ± 7, 61% men, 79% White, and 8% Hispanic). The 30-day and 90-day readmission rates were 28% and 47%, respectively, and 13% died at 90 days. Prediction for 30-day readmission resulted in 0.60 AUC for all patients with RFC, 0.57 AUC with LR for women-only subpopulation, and 0.61 AUC with LR for men-only subpopulation. For 90-day readmission, the highest AUC was achieved with kernel SVM and RFC (AUC = 0.62). We observed higher predictive value when training models with only women (AUC = 0.68 LR) vs men (AUC = 0.62 kernel SVM). Prediction for death resulted in 0.67 AUC for all patients, 0.72 for women-only subpopulation, and 0.69 for men-only subpopulation, all with LR. MELD-Na model AUC was similar to those from the AI models. DISCUSSION: Despite using multiple AI techniques, it is difficult to predict 30- and 90-day readmissions and death in cirrhosis. AI model accuracies were equivalent to models generated using only MELD-Na scores. Additional biomarkers are needed to improve our predictive capability (See also the visual abstract at http://links.lww.com/AJG/B710).

Background: Myocardial bridging (MB) is commonly treated in patients with hypertrophic cardiomyopathy (HCM). However, whether and how MB should be treated in patients with hypertrophic obstructive cardiomyopathy (HOCM) who underwent septal myectomy remain unclear. Methods: A total of 823 adults with HOCM who underwent septal myectomy at the Fuwai Hospital from 2011 to 2017 were retrospectively studied. Results: Overall, 31 events occurred: 24 patients died and 7 had nonfatal myocardial infarction (MI). The 3-year cumulative event-free survival of all-cause death (97.9% vs 100% vs 100% vs 98.4%, p=0.89) and cardiovascular death (98.3% vs 100% vs 100% vs 98.4%, p=0.63) were similar among the four groups (non-MB, CABG, unroofing, untreated, respectively). The 3-year cumulative event-free survival of nonfatal MI (100% vs 97.5% vs 98.0% vs 89.9%, p<0.001) and combined endpoints (97.9% vs 97.5% vs 98.0% vs 88.4%, p=0.02) were significantly lowest in untreated MB. Cox regression analysis indicated that untreated MB was a significant independent predictor of combined endpoints (hazard ratio [HR]: 4.06, 95% confidence interval [CI]: 1.60–10.32, p<0.001). Moreover, 49 patients underwent coronary artery computed tomography after surgery. The patency rate of the saphenous vein graft (SVG) was significantly higher than that of the left internal mammary artery (LIMA) (13.3% vs 84.2%, p<0.001). No MB was detected in the unroofing group. Conclusions: Surgical MB treatment could be beneficial and performed safely during septal myectomy. Myocardial unroofing is the recommended treatment for MB, and unroofing when technically possible may be preferable for long-term outcomes.

AbstractBackgroundObstructive sleep apnea (OSA) is a common disease associated with worse structural and functional impairment of the heart in patients with hypertrophic obstructive cardiomyopathy (HOCM).HypothesisThe presence and severity of OSA can decrease the right ventricular ejection fraction (RVEF) in patients with HOCM.MethodsIn total, 151 consecutive patients with a confirmed diagnosis of HOCM at Fuwai Hospital between September 2017 and September 2018 were included. Polysomnography and cardiac magnetic resonance imaging were performed in all patients.ResultsOverall, 84 (55.6%) patients were diagnosed with OSA. The RVEF significantly decreased with the severity of OSA (none, mild, moderate‐severe: 46.1 ± 8.2 vs 42.9 ± 7.5 vs 41.4 ± 7.4, P = .009). The apnea‐hypopnea index (AHI) was significantly high in patients with RVEF<40% among the different OSA groups (mild, moderate:7.7 ± 2.4 vs 9.6 ± 2.9, P = .03; 24.4 ± 9.0 vs 36.3 ± 18.0, P = .01). In the multiple linear regression model, the right ventricular end‐systolic volume (β = −0.28, P < .001), AHI (β = −0.09, P = .02), and oxygen desaturation index (β = −0.11, P = .04) were independently associated with a decrease in RVEF (adjusted R2 = 0.347, P < .001). Furthermore, the prevalence of RVEF<40% was high in patients with OSA. Compared with RVEF>40%, RVEF<40% was associated with more symptoms, mainly chest pain, chest distress, NYHA class III or IV, pulmonary hypertension, and moderate or severe mitral regurgitation.ConclusionIn patients with HOCM, the presence and severity of OSA is independently associated with a lower RVEF. In addition, compared with patients with RVEF>40%, those with RVEF<40% had more symptoms, including chest pain, chest distress, and NYHA class III or IV.

AbstractHeart regeneration occurs by dedifferentiation and proliferation of pre-existing cardiomyocytes (CMs). However, the signaling mechanisms by which injury induces CM renewal remain incompletely understood. Here, we find that cardiac injury in zebrafish induces expression of the secreted Wnt inhibitors, including Dickkopf 1 (Dkk1), Dkk3, secreted Frizzled-related protein 1 (sFrp1), and sFrp2, in cardiac tissue adjacent to injury sites. Experimental blocking of Wnt activity via Dkk1 overexpression enhances CM proliferation and heart regeneration, whereas ectopic activation of Wnt8 signaling blunts injury-induced CM dedifferentiation and proliferation. Although Wnt signaling is dampened upon injury, the cytoplasmic β-catenin is unexpectedly increased at disarrayed CM sarcomeres in myocardial wound edges. Our analyses indicated that p21-activated kinase 2 (Pak2) is induced at regenerating CMs, where it phosphorylates cytoplasmic β-catenin at Ser 675 and increases its stability at disassembled sarcomeres. Myocardial-specific induction of the phospho-mimetic β-catenin (S675E) enhances CM dedifferentiation and sarcomere disassembly in response to injury. Conversely, inactivation of Pak2 kinase activity reduces the Ser 675-phosphorylated β-catenin (pS675-β-catenin) and attenuates CM sarcomere disorganization and dedifferentiation. Taken together, these findings demonstrate that coordination of Wnt signaling inhibition and Pak2/pS675-β-catenin signaling enhances zebrafish heart regeneration by supporting CM dedifferentiation and proliferation.

Abstract Background We aimed to develop a gene expression–based prognostic signature for isocitrate dehydrogenase (IDH) wild-type glioblastoma using clinical trial datasets representative of glioblastoma clinical trial populations. Methods Samples were collected from newly diagnosed patients with IDH wild-type glioblastoma in the ARTE, TAMIGA, EORTC 26101 (referred to as “ATE”), AVAglio, and GLARIUS trials, or treated at UCLA. Transcriptional profiling was achieved with the NanoString gene expression platform. To identify genes prognostic for overall survival (OS), we built an elastic net penalized Cox proportional hazards regression model using the discovery ATE dataset. For validation in independent datasets (AVAglio, GLARIUS, UCLA), we combined elastic net–selected genes into a robust z-score signature (ATE score) to overcome gene expression platform differences between discovery and validation cohorts. Results NanoString data were available from 512 patients in the ATE dataset. Elastic net identified a prognostic signature of 9 genes (CHEK1, GPR17, IGF2BP3, MGMT, MTHFD1L, PTRH2, SOX11, S100A9, and TFRC). Translating weighted elastic net scores to the ATE score conserved the prognostic value of the genes. The ATE score was prognostic for OS in the ATE dataset (P &lt; 0.0001), as expected, and in the validation cohorts (AVAglio, P &lt; 0.0001; GLARIUS, P = 0.02; UCLA, P = 0.004). The ATE score remained prognostic following adjustment for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and corticosteroid use at baseline. A positive correlation between ATE score and proneural/proliferative subtypes was observed in patients with MGMT non-methylated promoter status. Conclusions The ATE score showed prognostic value and may enable clinical trial stratification for IDH wild-type glioblastoma.

Abstract Background: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. Methods: We conducted a gene–environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case–control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. Results: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P &lt; 1.25 × 10−6) was observed in the meta-analysis (PGxE = 1.2 ×10−6, PJoint = 4.2 ×10−7). Conclusions: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. Impact: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.