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Supplementary Figure 1

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Supplementary Table S1

On November 21, 2018, the FDA approved glasdegib (Daurismo; Pfizer), a small-molecule Hedgehog inhibitor, in combination with low-dose cytarabine (LDAC) for treatment of newly diagnosed acute myeloid leukemia (AML) in adults ≥ 75 years or with comorbidities that preclude use of intensive induction chemotherapy. Evidence of clinical benefit came from Study BRIGHT AML 1003, a randomized trial comparing glasdegib+LDAC with LDAC alone for treatment of newly diagnosed AML in 115 patients either ≥ 75 years old or ≥ 55 years old with preexisting comorbidities. Efficacy was established by improved overall survival (OS) with the combination compared with LDAC alone (HR, 0.46; 95% confidence interval, 0.30–0.71; one-sided stratified log-rank P = 0.0002). Median OS was 8.3 months with the combination and 4.3 months with LDAC alone. Common adverse reactions included cytopenias, fatigue, hemorrhage, febrile neutropenia, musculoskeletal pain, nausea, edema, dyspnea, decreased appetite, dysgeusia, mucositis, constipation, and rash. The label includes a boxed warning for embryo-fetal toxicity and a warning for QT interval prolongation. There is a limitation of use for patients with moderate-to-severe hepatic and severe renal impairment; trials studying glasdegib in these patient populations are required as a condition of this approval.See related commentary by Fathi, p. 6015

We hypothesised that zanubrutinib, a highly selective next-generation Bruton tyrosine kinase (BTK) inhibitor, would be a safe and active treatment for patients intolerant of ibrutinib, acalabrutinib, or both. We aimed to assess whether zanubrutinib would prolong treatment duration by minimising treatment-related toxicities and discontinuations in patients with previously treated B-cell malignancies.This ongoing, phase 2, multicentre, open-label, single-arm study was done in 20 centres in the USA. Patients aged 18 or older with previously treated B-cell malignancies (chronic lymphocytic leukaemia, small lymphocytic lymphoma, mantle cell lymphoma, Waldenström macroglobulinaemia, or marginal zone lymphoma) who became intolerant of ibrutinib, acalabrutinib, or both, were orally administered zanubrutinib 160 mg twice daily or 320 mg once daily per investigator. The primary endpoint was recurrence and change in severity of ibrutinib or acalabrutinib intolerance events based on investigator-assessed adverse events. Secondary endpoints were investigator-assessed overall response rate; duration of response; disease control rate; and progression-free survival. Analyses included all patients who received any dose of the study drug. This study is registered with ClinicalTrials.gov, NCT04116437.Between Oct 14, 2019, and Sept 8, 2021, 67 patients (36 [54%] men and 31 [46%] women) who were intolerant of ibrutinib (n=57; cohort 1) or of acalabrutinib or acalabrutinib and ibrutinib (n=10; cohort 2) were enrolled. 63 (94%) patients were White, one (2%) had multiple ethnicities, and three (5%) had unreported or unknown ethnicity. Most intolerance events (81 [70%] of 115 for ibrutinib; 15 [83%] of 18 for acalabrutinib) did not recur with zanubrutinib. Of the recurring events, seven (21%) of 34 ibrutinib intolerance events and two (67%) of three acalabrutinib intolerance events recurred at the same severity with zanubrutinib; 27 (79%) ibrutinib intolerance events and one (33%) acalabrutinib intolerance event recurred at a lower severity with zanubrutinib. No events recurred at higher severity. No grade 4 intolerance events recurred. 64 (96%) of 67 patients had one or more adverse events with zanubrutinib; the most common adverse events were contusion (in 15 [22%] of 67 patients), fatigue (14 [21%]), myalgia (ten [15%]), arthralgia (nine [13%]), and diarrhoea (nine [13%]). Atrial fibrillation occurred in three (4%) patients (all grade 2). Eight (12%) of 67 patients had serious adverse events (anaemia, atrial fibrillation, bronchitis, COVID-19, COVID-19 pneumonia, febrile neutropenia, salmonella gastroenteritis, transfusion reaction, trigeminal nerve disorder, and urinary tract infection). No treatment-related deaths occurred. The median follow-up time was 12·0 months (IQR 8·2-15·6). Among the 64 efficacy-evaluable patients, disease control rate was 93·8% (60; 95% CI 84·8-98·3) and overall response rate was 64·1% (41; 95% CI 51·1-75·7). The median duration of response was not reached; the 12-month event-free duration of response rate was 95·0% (95% CI 69·5-99·3). Similarly, median progression-free survival was not reached; 18-month progression-free survival was 83·8% (95% CI 62·6-93·6).Patients intolerant of previous BTK inhibitors have limited treatment options. These results suggest that zanubrutinib, a safe and viable treatment for patients with B-cell malignancies, might fill that unmet need for those who exhibit intolerance to ibrutinib or acalabrutinib.BeiGene.

Background: Bruton tyrosine kinase inhibitors (BTKis) are important tools to treat B-cell malignancies. However, duration of treatment may be limited by adverse events (AEs). Zanubrutinib (zanu) is a BTKi approved for mantle cell lymphoma (MCL) and is in development for other hematologic malignancies. Data from phase 3 head-to-head trials of zanu vs ibrutinib (ibr) in pts with Waldenström macroglobulinemia (WM) or chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) demonstrated that pts treated with zanu showed lower rates of AEs leading to discontinuation (Blood 2020;136(18):2038-50; EHA 2021 LB1900). Preliminary results from BGB-3111-215 (NCT04116437) show that zanu was well-tolerated in pts who discontinued ibr and/or acalabrutinib (acala) treatment due to AEs (EHA 2021 EP642). Here, we report updated results from the BGB-3111-215 study with a median follow-up of 9 months. Methods: This study is an ongoing US, phase 2, multicenter, single-arm, open-label study. The safety and efficacy of zanu monotherapy (160 mg twice daily or 320 mg once daily) were evaluated in pts with B-cell malignancies who met criteria for continued treatment after having become intolerant to prior BTKi therapy. Pts were divided into cohort 1 (pts who were intolerant to ibr only) and cohort 2 (pts who were intolerant to acala alone/and ibr). Pts with documented progressive disease (PD) on prior BTKi therapy were excluded. Efficacy and safety, including recurrence of intolerant AEs to the prior BTKi, were evaluated. AEs were assessed for severity, seriousness, and relation to zanu; as well as dose reductions, holds, or discontinuations. Response was assessed by investigators based on response criteria for their respective indications (Blood 2008;131:2745; J Clin Oncol 2012;30:2820; J Clin Oncol 2014;32:3059; Br J Haemtol 2013;160:171). Disease parameters from study entry were the baseline for response assessment. Mutational analysis was performed on pts who discontinued treatment, and data will be shared once available. To support clinical findings, kinase selectivity was assessed using Kinome profiling at 100X IC50 (against BTK) for zanu, ibr, acala and its major metabolite, M27 (Reaction Biology Corp). Results: As of 7 June 2021 (data cutoff), 57 pts (n=44 CLL/SLL; n=9 WM; n=2 MCL; n=2 marginal zone lymphoma [MZL]) were enrolled in cohort 1, and 7 pts were enrolled in cohort 2 (n=4 CLL; n=1 WM; n=1 MCL; n=1 MZL). All received ≥1 dose of zanu and were analyzed for safety. The median age was 71 years (range, 49-91) in cohort 1 and 71 years (range, 65-76) in cohort 2; median duration of treatment was 8.7 months (range, 0.6-17.9) in cohort 1 and 8.2 months (range, 6.4-11.4) in cohort 2; median number of prior regimens was 1 (range, 1-12) in cohort 1 and 3 (range, 2-5) in cohort 2. Within cohort 2, 5 pts were intolerant to both ibr and acala. Median number of intolerant events per pt for both cohorts 1 and 2 was 2 (range, 1-5). Overall, 73% of pts did not experience recurrence of their ibr or acala intolerant events and 79% of recurrent events recurred at a lower severity (Figure 1). At cutoff, 54 pts remained on treatment. Reasons for treatment discontinuation were AEs (n=4), PD (n=4), physician's decision (n=1), and consent withdrawal (n=1). Grade ≥3 AEs were reported in 18 pts (28%), and serious AEs occurred in 7 pts (11%). AEs requiring dose interruptions occurred in 17 pts (27%), and AEs leading to dose reduction occurred in 3 pts (5%). One death, due to COVID-19, was reported. Pts demonstrated maintained (41%) and improved (53%) response with zanu treatment from their reported best overall response on prior BTKis for a total disease control rate of 94% (including a 42% partial response rate in pts with CLL/SLL, 30% in pts with WM, and a 20% very good partial response rate in pts with WM). Zanu also demonstrated good selectivity by kinase profiling. It showed >50% inhibition on 7/370 kinases, while ibr, acala, and M27 had more off-target binding (17, 15 and 23 kinases, respectively) at their respective 100X IC50 (BTK) concentrations (Figure 2). Conclusion: In pts with B-cell malignancies intolerant to ibr and/or acala, zanu treatment resulted in continued disease control or improved response. Zanu was well-tolerated, and most AEs that led to discontinuation of previous BTKi therapy did not recur or recurred at a lower grade. In support of clinical findings, differentiation between BTKi selectivity profiles favor zanu over ibr and acala. Figure 1 Figure 1. Disclosures Shadman: Abbvie, Genentech, AstraZeneca, Sound Biologics, Pharmacyclics, Beigene, Bristol Myers Squibb, Morphosys, TG Therapeutics, Innate Pharma, Kite Pharma, Adaptive Biotechnologies, Epizyme, Eli Lilly, and Atara Biotherapeutics, Adaptimmune: Consultancy; Mustang Bio, Celgene, Bristol Myers Squibb, Pharmacyclics, Gilead, Genentech, Abbvie, TG Therapeutics, Beigene, AstraZeneca, Sunesis, Atara Biotherapeutics, GenMab: Research Funding; Abbvie, Genentech, AstraZeneca, Sound Biologics, Pharmacyclics, Beigene, Bristol Myers Squibb, Morphosys, TG Therapeutics, Innate Pharma, Kite Pharma, Adaptive Biotechnologies, Epizyme, Eli Lilly, and Atara Biotherapeutics, Adaptimmune: Membership on an entity's Board of Directors or advisory committees. Flinn: Nurix Therapeutics: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Seagen: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; MorphoSys: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Forty Seven: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Calithera Biosciences: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Verastem: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Curis: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Takeda: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Yingli Pharmaceuticals: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; IGM Biosciences: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; AbbVie: Consultancy, Other: All Consultancy and Research Funding payments made to Sarah Cannon Research Institute, Research Funding; Portola Pharmaceuticals: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Trillium Therapeutics: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Rhizen Pharmaceuticals: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Incyte: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Acerta Pharma: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Agios: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Kite, a Gilead Company: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Gilead Sciences: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Karyopharm Therapeutics: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Forma Therapeutics: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Genentech: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; ArQule: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Triphase Research & Development Corp.: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Roche: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Pfizer: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Teva: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Infinity Pharmaceuticals: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Unum Therapeutics: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Celgene: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Constellation Pharmaceuticals: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Juno Therapeutics: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; AstraZeneca: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Iksuda Therapeutics: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Loxo: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Merck: Other: All research funding payments made to Sarah Cannon Research Institute, Research Funding; Novartis: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Great Point Partners: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; BeiGene: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Janssen: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; TG Therapeutics: Consultancy, Other: All consultancy and research funding payments made to Sarah Cannon Research Institute, Research Funding; Century Therapeutics: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Hutchison MediPharma: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Vincerx Pharma: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Sarah Cannon Research Institute: Current Employment; Servier Pharmaceuticals: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Yingli Pharmaceuticals: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Seagen: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Servier Pharmaceuticals: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute; Unum Therapeutics: Consultancy, Other: All consultancy payments made to Sarah Cannon Research Institute, Research Funding; Johnson & Johnson: Current holder of individual stocks in a privately-held company; Seattle Genetics: Research Funding. Levy: Epizyme: Consultancy, Other: Promotional speaker; Amgen Inc.: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau; Gilead Sciences, Inc.: Consultancy, Honoraria, Speakers Bureau; GSK: Consultancy, Other: Promotional speaker; Morphosys: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau; Beigene: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau; Novartis: Consultancy, Other: Promotional speaker; Dova: Consultancy, Other: Promotional speaker; TG Therapeutics: Consultancy, Honoraria, Speakers Bureau; Bristol Myers Squibb: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Honoraria, Speakers Bureau; Janssen Pharmaceuticals: Consultancy, Honoraria, Other: Promotional speaker, Speakers Bureau. Burke: SeaGen: Consultancy, Speakers Bureau; Beigene: Consultancy, Speakers Bureau; MorphoSys: Consultancy; Bristol Myers Squibb: Consultancy; AstraZeneca: Consultancy; Epizyme: Consultancy; Verastem: Consultancy; Kura: Consultancy; Kymera: Consultancy; AbbVie: Consultancy; Adaptive Biotechnologies: Consultancy; Roche/Genentech: Consultancy; X4 Pharmaceuticals: Consultancy. Cultrera: Beigene: Research Funding. Yimer: Astrazeneca: Speakers Bureau; Karyopharm: Current equity holder in publicly-traded company, Speakers Bureau; Janssen: Speakers Bureau; Beigene: Speakers Bureau; GSK: Speakers Bureau; Sanofi: Speakers Bureau; Amgen: Speakers Bureau; Pharmacyclics: Speakers Bureau; Texas Oncology: Current Employment. Chaudhry: Medical Oncology Associates, PS (dba Summit Cancer Centers): Current Employment; Novartis, Immunomedics: Current holder of individual stocks in a privately-held company. Gandhi: TG Therapeutics: Honoraria; Karyopharm Therapeutics: Honoraria; GlaxoSmithKline: Honoraria. Kingsley: Comprehensive Cancer Centers of Nevada: Current Employment. Tumula: Texas Oncology: Current Employment. Manda: Morphosys: Honoraria; Genmab: Current equity holder in publicly-traded company. Chen: BeiGene: Current Employment, Divested equity in a private or publicly-traded company in the past 24 months. Cohen: BeiGene: Current Employment, Current equity holder in publicly-traded company, Other: Travel, Accommodations, Expenses. By: BeiGene, Ltd: Current Employment. Xu: Beigene: Current Employment; AstraZeneca: Ended employment in the past 24 months. Liu: BeiGene Co., Ltd: Current Employment, Current equity holder in publicly-traded company. Sharman: TG Therapeutics: Consultancy; Centessa: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics LLC, an AbbVie Company: Consultancy; BMS: Consultancy; AbbVie: Consultancy; BeiGene: Consultancy; AstraZeneca: Consultancy; Lilly: Consultancy.

Purpose Abuse, misuse, addiction, overdose, and death associated with non-medical use of prescription opioids have become a serious public health concern. Reformulation of these products with abuse-deterrent properties is one approach for addressing this problem. FDA has approved several extended-release opioid analgesics with abuse-deterrent labeling, the bases of which come from pre-market studies. As all opioid analgesics must be capable of delivering the opioid in order to reduce pain, abuse-deterrent properties do not prevent abuse, nor do pre-market evaluations ensure that there will be reduced abuse in the community. Utilizing data from various surveillance systems, some recent post-market studies suggest a decline in abuse of extended-release oxycodone after reformulation with abuse-deterrent properties. We discuss challenges stemming from the use of such data. Methods We quantify the relationship between the sample, the population, and the underlying sampling mechanism and identify the necessary conditions if valid statements about the population are to be made. The presence of other interventions in the community necessitates the use of comparators. We discuss the principles under which the use of comparators can be meaningful. Conclusions Results based on surveillance data need to be interpreted with caution as the underlying sampling mechanisms can bias the results in unpredictable ways. The use of comparators has the potential to disentangle the effect due to the abuse-deterrence properties from those due to other interventions. However, identifying a comparator that is meaningful can be very difficult.

On November 21, 2018, the FDA approved glasdegib (Daurismo; Pfizer), a small-molecule Hedgehog inhibitor, in combination with low-dose cytarabine (LDAC) for treatment of newly diagnosed acute myeloid leukemia (AML) in adults ≥ 75 years or with comorbidities that preclude use of intensive induction chemotherapy. Evidence of clinical benefit came from Study BRIGHT AML 1003, a randomized trial comparing glasdegib+LDAC with LDAC alone for treatment of newly diagnosed AML in 115 patients either ≥ 75 years old or ≥ 55 years old with preexisting comorbidities. Efficacy was established by improved overall survival (OS) with the combination compared with LDAC alone (HR, 0.46; 95% confidence interval, 0.30–0.71; one-sided stratified log-rank P = 0.0002). Median OS was 8.3 months with the combination and 4.3 months with LDAC alone. Common adverse reactions included cytopenias, fatigue, hemorrhage, febrile neutropenia, musculoskeletal pain, nausea, edema, dyspnea, decreased appetite, dysgeusia, mucositis, constipation, and rash. The label includes a boxed warning for embryo-fetal toxicity and a warning for QT interval prolongation. There is a limitation of use for patients with moderate-to-severe hepatic and severe renal impairment; trials studying glasdegib in these patient populations are required as a condition of this approval. See related commentary by Fathi, p. 6015

6509 Background: Recent evidence suggests that treatment with systemic antibiotics (Abx) disrupts the intestinal microbiome and may be associated with decreased survival for patients receiving treatment with ICIs for advanced cancers, including R/M HNSCC. However, a potential confounder is that Abx use identifies a subgroup of patients with a worse prognosis. The FDA examined the association between Abx use and survival for ICIs and other drugs used for the treatment of patients with R/M HNSCC. Methods: Data submitted to the FDA from three randomized controlled trials with ICI as a single agent or with chemotherapy (ICI group) compared to chemotherapy and/or cetuximab (Control group) were pooled. The association between systemic Abx use within 30 days of initiating anticancer therapy and survival for the ICI and Control groups was evaluated using Kaplan-Meier (KM) estimates and compared using Cox proportional hazards regression models, controlling for ECOG performance status, line of therapy, HPV status, PD-L1 expression, and other important prognostic factors. Results: In the ICI and Control groups, 36% and 46% of patients received Abx, respectively. For the ICI group, the difference in KM-estimated median overall survival (OS) was 5.6 months based on receipt of Abx (hazard ratio [HR] 1.70). Abx had no impact on OS for the Control group. Similar trends were observed for progression-free survival (PFS). Conclusions: In this exploratory analysis, systemic Abx within 30 days of initiating treatment for R/M HNSCC was associated with decreased survival for patients treated with ICIs compared with patients who did not receive Abx. Use of Abx had no apparent difference in survival in the control group. Further examination of the association between Abx use and clinical outcomes for patients with R/M HNSCC treated with ICIs is needed. [Table: see text]

Background An increased incidence of prostate cancer was observed in Parkinson's disease (PD) patients treated with entacapone during a pre-approval randomized clinical trial; the relation has not been robustly investigated in the U.S. ambulatory setting. Objective To investigate whether entacapone is associated with prostate cancer and to assess whether the associations are correlated with advanced disease at the time of cancer diagnosis. Methods Using data from the Department of Veterans Affairs healthcare system, new-user cohorts were created of PD patients treated with add-on entacapone or add-on dopamine agonist/monoamine oxidase B inhibitors between January 2000 and December 2014. Patients were followed on-treatment for occurrence of prostate cancer, identified via linkage to the VA cancer registry. Results Mean follow-up time was 3.1 and 4.0 years in the entacapone and control cohort, respectively. There were 17,666 subjects meeting study criteria (mean age, 74 (SD 8.6) years); the entacapone-treated group comprised 5,257 subjects. Twenty-three prostate cancer cases occurred in the entacapone cohort and ninety-seven in the control cohort. The overall incidence of prostate cancer was 1.8 per 1,000 person-years of risk. There was no difference in risk of prostate cancer between the cohorts for increased duration of entacapone intake (adjusted HR: 1.08; 95% confidence interval: 0.46–2.51 for cumulative exposure of ≥2 years). Time since starting drug therapy and cumulative dose (mg) also do not suggest a difference in prostate cancer risk between cohorts. Conclusions Prolonged therapy with entacapone was not associated with increased prostate cancer incidence; however, findings suggest a higher severity of prostate cancer.

Purpose To compare cardiovascular and mortality risks in elderly patients treated with varenicline or bupropion for smoking cessation. Methods Elderly Medicare beneficiaries were entered into new-user cohorts of varenicline or bupropion for smoking cessation and followed on therapy for primary outcomes of acute myocardial infarction (AMI), stroke, mortality, and a composite of any of these events. Secondary outcomes were unstable angina, coronary revascularization, and a composite of any primary or secondary outcome event. Propensity score stratification was used to adjust for baseline differences in potential confounding factors. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using Cox proportional hazards, with bupropion as reference. Results In cohorts of 74 824 varenicline and 14 133 bupropion users, there were 164 AMI, 96 stroke, 87 death, 317 primary composite, and 814 secondary composite events while on therapy. The HRs (95%CI) were 0.79 (0.50–1.24) for AMI, 1.27 (0.63–2.55) for stroke, 0.58 (0.30–1.13) for death, 0.84 (0.58–1.23) for the primary composite, and 0.92 (0.73–1.14) for the secondary composite. The risk of AMI or the primary composite outcome did not differ in subgroups defined by age, diabetes status, or presence of underlying ischemic heart disease. Only 30% of patients remained on either study drug beyond their first prescription. Conclusion Cardiovascular and mortality risks were not increased in older patients treated with varenicline compared with bupropion for smoking cessation. A potential increase in the risk of stroke with varenicline could not be excluded. Treatment persistence with either drug was low. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

This article describes a new software for modeling correlated binary data based on orthogonalized residuals, a recently developed estimating equations approach that includes, as a special case, alternating logistic regressions. The software is flexible with respect to fitting in that the user can choose estimating equations for association models based on alternating logistic regressions or orthogonalized residuals, the latter choice providing a non-diagonal working covariance matrix for second moment parameters providing potentially greater efficiency. Regression diagnostics based on this method are also implemented in the software. The mathematical background is briefly reviewed and the software is applied to medical data sets.

Background: Multiple novel therapies have been approved for the treatment of RRMM in recent years, resulting in improvements in progression free survival (PFS) and overall survival (OS). However, clinical trials in MM often enroll only a small proportion of older patients, particularly patients ≥75 years (Kanapuru 2017). Evaluating the impact of novel therapies, especially triplet therapies, in older adults with RRMM from individual clinical trials is challenging due to the small sample size. Furthermore, significant heterogeneity exists among the older adult population with regards to tolerability of anti-myeloma therapy. In newly diagnosed transplant-ineligible patients with MM, evidence from pooled analysis indicates that patients >80 years may be at increased risk for adverse clinical outcomes (Palumbo 2015). We evaluated the prognostic impact of age on survival outcomes in patients with RRMM receiving novel therapies. Methods: Data from 10 clinical trials submitted for approval between 2011-2015 were pooled for this analysis. Participants were grouped according to four age strata: 80 years. PFS and OS were calculated using the Kaplan-Meier method (K-M). Within each age stratum, we conducted a subgroup analysis comparing doublet versus triplet regimens. Cox's proportional hazards regression model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for gender, race, ISS stage, ECOG status, regimen (only for primary age analysis) and prior transplant. Results: In total, 4766 patients were included in the analysis. Forty-seven percent were 80 years of age. The percentage of patients with baseline ISS stage III and ECOG 2 was higher in the 75-80 years (31.0% and 11.0%) and >80 years group (32.0%, 19.0%) compared to 65-74 years (24.0%, 8.0%) and Adjusted PFS HR (95% CI) for triplet versus doublet regimens was 0.69 (0.60, 0.79), 0.71 (0.61, 0.83), 0.61 (0.46, 0.81), and 0.62 (0.36, 1.05) for 80 years respectively. The HR (95% CI) for OS was 0.70 (0.59, 0.83), 0.86 (0.72, 1.02), 0.55 (0.40, 0.77) and 0.98 (0.56, 1.73). Conclusions: Improvement in PFS with novel therapies, including triplet regimens, appears to extend to older adults including patients >80 years of age. No trend in treatment effect for PFS was observed across the age groups. Overall survival was lower in adults ≥65 years of age compared to patients 80 years of age. Triplet regimens appear to improve survival over doublet regimens; however, a consistent trend across age groups was not observed. The OS results from this analysis must be interpreted with caution due to immature OS data at the time of submission, differential follow-up for individual trials, and small sample size, particularly in patients >80 years of age. Enrolling a representative population of older adults in MM clinical trials is needed to allow for an accurate assessment of outcomes in this population. Furthermore, considering biologic age rather than chronologic age to identify older patients who can benefit from these therapies would serve to further advance treatment in patients with MM. Disclosures No relevant conflicts of interest to declare.

2516 Background: Many studies exhibit what seems to be dis-proportionately higher early mortality (EM) in anti-PD-1/PD-L1 containing arms (IO) when compared to active control arms (AC), resulting in early crossing of the Kaplan-Meier overall survival curves. We examine if EM with the use of IO is specific to certain demographic and disease characteristics. Methods: Data from 16 randomized AC trials submitted to FDA containing 6055 IO and 3604 AC patients in HNSCC, Melanoma, NSCLC, RCC, and Urothelial Carcinoma were evaluated for signs of EM. Study-specific and pooled piecewise hazard ratios (HRs) were used to quantify EM from 0 to 60 and > 60 days. Additionally, HRs up to 60 days were used to assess the extent specific subgroups account for EM. Results: Piecewise HRs comparing OS between IO and AC changed direction, > 1 to < 1 in 11 trials; melanoma (5/6), NSCLC (3/7), HNSCC (1/1), RCC (1/1), and urothelial cancer (1/1). When pooled, NSCLC studies retained this EM pattern, although attenuated, with HR (95% CI) of 1.12 (0.91, 1.38) ≤60 days and 0.66 (0.61, 0.72) after 60 days. This was not observed in the pooled melanoma studies: 0.88 (0.63, 1.24) ≤ 60 days and 0.59 (0.53, 0.67) after 60 days. EM in both arms was associated with poor ECOG performance status (PS), increased LDH, and high tumor burden. Comparing EM patients in the IO and AC arms, a larger proportion were female in the melanoma trials (41% vs. 28%), a smaller proportion had squamous histology in the NSCLC trials (32% vs. 41%), and a larger proportion were PD-L1 negative (56% vs. 36% melanoma; 60% vs. 43% NSCLC). Analysis of the pooled melanoma studies suggests PD-L1 negative melanoma patients with high baseline tumor burden and PS played a role in EM with HR before 60 days of 1.49 (0.75, 2.97). However, these results were not reproducible in NSCLC. Conclusions: Potential risk factors for EM were assessed in individual and pooled trials. While several factors—negative PD-1/PD-L1 status and high ECOG, LDH and tumor burden—seem to play a role in EM, these high-risk subgroups do not fully explain the EM patterns observed in the IO treated patients.

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts.

Background: Multiple myeloma (MM) is a disease of older adults with a median age of onset of 70 years. Approximately 20% of the incident cases are diagnosed in patients 85 years and older. There is significant heterogeneity among older adults with regards to the tolerability of myeloma directed therapy. In newly diagnosed transplant ineligible patients with MM, available evidence indicates that age greater than 80 is an independent risk factor for adverse clinical outcomes ("frail"). However, there are limited data on outcomes in adults 80 years and older in the relapsed or refractory disease setting. Over the past few years, the therapy armamentarium for patients with relapsed or refractory MM has expanded considerably with approval of at least 5 new drugs including two monoclonal antibodies, an HDAC inhibitor, and an oral proteasome inhibitor. The impact of these recent drug approvals on clinical outcomes in adults 80 years and older with relapsed or refractory MM is also unknown. This pooled analysis attempts to evaluate outcomes by age in patients with relapsed or refractory multiple myeloma Methods: Data from 10 clinical trials submitted to support approval of drugs for patients with relapsed or refractory multiple myeloma from 2011-2018 were pooled for this analysis. Participants were grouped according to three age strata: 80 years. Clinical outcomes including response rates (ORR, CR, and PR) in the different age groups were analyzed. Preliminary results of response rates by age are presented. Results: We identified 4766 patients enrolled in 10 clinical trials of relapsed or refractory multiple myeloma. The median age of the patient population was 64.5 (range 30.0-91.0). Eighty-five percent of the patients were less than 75 years of age, 11% were between 75-80 years of age, and only 4% were older than 80 years of age. Seventy percent of the population was classified as ISS Stage I or II and 24% was ISS Stage III. Overall response rate (ORR) in the pooled studies was 69% (67.6, 70.2) with less than 15% of the responses being complete responses (CR). ORR was 63.3 % (55.6, 70.6) in those 80 years and older; 70.6 % (66.6, 74.5) in the 75-80 years age group; and 68.9 % (67.5, 70.4) in patients younger than 75 years of age. CR rates were 8.3% in both the 75-80 age group and those older than 80 years, and 14.0% in those younger than 75 years. Conclusion: In this large database of recent approvals for the treatment of RRMM, preliminary results show no significant differences in ORR between patients over 80 years and those 80 years and younger (difference -5.4%; 95% CI (-13.1%, 2.3%)) suggesting response to treatment is independent of age. However, our results need to be interpreted with caution considering differences in patient populations particularly with respect to different treatment regimens and therapies. Analysis of survival outcomes is ongoing. Table. Table. Disclosures No relevant conflicts of interest to declare.

Background: An increased risk of prostate cancer was observed in Parkinson’s disease (PD) patients treated with entacapone during a pre-approval randomized clinical trial. Objective: To investigate a potential association between entacapone use and prostate cancer in an ambulatory setting. Methods: Using data from the Department of Veterans Affairs (VA) healthcare system, new-user cohorts were created of PD patients treated with add-on entacapone or add-on dopamine agonist/monoamine oxidase B inhibitors between January 2000 and December 2014. Patients were followed on-treatment for occurrence of prostate cancer, identified via VA cancer registry linkage. Cox proportional hazards regression with time-dependent exposure was used to calculate hazard ratios (HR) and 95% confidence intervals (CI). Confounding was controlled by using inverse probability treatment weighting calculated from propensity scores. Results: Mean follow-up time was 3.1 and 4.0 years in the entacapone and control cohort, respectively. There were 17,666 subjects meeting study criteria (mean age, 74 (SD 8.6) years); the group treated with entacapone comprised 5,257 subjects. Twenty-three prostate cancers occurred in the entacapone cohort and 97 in the control cohort. The overall incidence of prostate cancer was 1.8 per 1000 person-years of risk. There was no difference in risk of prostate cancer between the cohorts for increased duration of entacapone intake (adjusted HR: 1.08; 95% confidence interval: 0.46-2.51 for cumulative exposure of ≥2 years). Time since starting drug therapy and cumulative dose (mg) were also examined. Conclusion: In this cohort of PD patients, extended duration of entacapone use was not associated with an increased incidence of prostate cancer. Note: This abstract was not presented at the meeting. Citation Format: Jacqueline M. Major, Francesca Cunningham, Diane Dong, Kunthel By, Kwan Hur, David C. Shih, Simone P. Pinheiro, Gerald D. Podskalny, David J. Graham. Entacapone and prostate cancer in patients with Parkinson’s disease: A large Veterans Health Administration study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2303. doi:10.1158/1538-7445.AM2017-2303

To compare cardiovascular and mortality risks in elderly patients treated with varenicline or bupropion for smoking cessation.Elderly Medicare beneficiaries were entered into new-user cohorts of varenicline or bupropion for smoking cessation and followed on therapy for primary outcomes of acute myocardial infarction (AMI), stroke, mortality, and a composite of any of these events. Secondary outcomes were unstable angina, coronary revascularization, and a composite of any primary or secondary outcome event. Propensity score stratification was used to adjust for baseline differences in potential confounding factors. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using Cox proportional hazards, with bupropion as reference.In cohorts of 74 824 varenicline and 14 133 bupropion users, there were 164 AMI, 96 stroke, 87 death, 317 primary composite, and 814 secondary composite events while on therapy. The HRs (95%CI) were 0.79 (0.50-1.24) for AMI, 1.27 (0.63-2.55) for stroke, 0.58 (0.30-1.13) for death, 0.84 (0.58-1.23) for the primary composite, and 0.92 (0.73-1.14) for the secondary composite. The risk of AMI or the primary composite outcome did not differ in subgroups defined by age, diabetes status, or presence of underlying ischemic heart disease. Only 30% of patients remained on either study drug beyond their first prescription.Cardiovascular and mortality risks were not increased in older patients treated with varenicline compared with bupropion for smoking cessation. A potential increase in the risk of stroke with varenicline could not be excluded. Treatment persistence with either drug was low. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.