Shi, Qian

Given the Food and Drug Administration's (FDA's) acceptance of master protocol designs in recent guidance documents, the oncology field is rapidly moving to address the paradigm shift to molecular subtype focused studies. Identifying new “marker‐based” treatments requires new methodologies to address the growing demand to conduct clinical trials in smaller molecular subpopulations, identify effective treatment and marker interactions, and control for false positives. We introduce our methodology, Hierarchical Bayesian Clustering Design of Multiple Biomarker Subgroups (HCOMBS), a two‐stage umbrella Phase II design with effect size clustering and information borrowing across multiple biomarker‐treatment pairs. HCOMBS was designed to reduce required sample size, differentiate between varying effect sizes, and control for operating characteristics in the multi‐arm setting. When compared to independently applied Simon's Optimal two‐stage design, we showed through simulations that HCOMBS required less participants per treatment arm with a well‐controlled family‐wise error rate and desirable marginal power. Additionally, HCOMBS features a statistical approach that simultaneously conducts clustering and hypothesis testing in one step. We also applied the proposed design on the alliance brain metastases umbrella trial.

Abstract Limited data exist to describe the clinical features and outcomes for elderly patients with follicular lymphoma (FL). The Follicular Lymphoma Analysis of Surrogacy Hypothesis (FLASH) group performed a prospectively planned pooled analysis of individual patient data from first-line randomized controlled trials (RCTs) and examined associations between age (≤70 vs >70 years), clinical characteristics, and FL outcomes. We identified 18 multicenter clinical RCTs in the FLASH database that enrolled elderly patients (>70 years). Primary end points were early disease outcomes, CR24 and CR30, and progression-free survival (PFS) at 24 months (PFS24). Secondary end points were PFS and overall survival (OS). We identified 5922 previously untreated FL patients from 18 RCTs. Patients age >70 years (vs ≤70 years) more commonly had elevated lactate dehydrogenase, hemoglobin <12 g/dL, ECOG PS ≥2, and elevated β2-microglobulin. Median follow-up was 5.6 years. Patients >70 years did not differ from patients ≤70 years in rates of CR24, CR30, or PFS24. With a median OS of 14.6 years for all patients, median OS was 7.4 and 15.7 years for patients >70 and ≤70 years of age, respectively (hazard ratio = 2.35; 95% confidence interval = 2.03-2.73; P < .001). Age >70 years was a significant predictor of OS and PFS due to higher rates of death without progression, but not PFS24, CR24, or CR30. FL patients >70 years 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.

Abstract Background First-line therapeutic strategies for patients with BRAFV600E-mutated (BRAFmt) metastatic colorectal cancer (mCRC) mainly rely on subgroup analyses from randomized controlled trials (RCTs). We aimed to assess the prognostic and predictive impact of BRAFmt on the efficacy of targeted therapies with first-line chemotherapy. Methods Individual patient data from first-line RCTs with BRAF and KRAS status data in the ARCAD database were pooled. Progression-free survival and overall survival (OS) were assessed using Kaplan-Meier and Cox models. Outcomes were compared between treatment groups that were concurrently randomly assigned whenever possible. Results A total of 6391 patients from 10 RCTs were included: 573 BRAFmt (9.0%), 2059 KRASmt (32.2%), and 3759 double wild type (58.8%). BRAFmt mCRC patients experienced statistically significantly poorer OS than those with KRASmt (adjusted hazard ratio [HRadj] = 1.46, 95% confidence interval [CI] = 1.30 to 1.64) and patients with double wild-type tumors (HRadj = 2.14, 95% CI = 1.94 to 2.36). Anti-EGFR agents did not improve progression-free survival or OS of BRAFmt mCRC patients, based on 4 RCTs testing chemotherapy with or without anti-epidermal growth factor receptor (anti-EGFR) (HRadj = 0.96, 95% CI = 0.71 to 1.30; and HRadj = 0.85, 95% CI = 0.66 to 1.14, respectively). Conclusions Our data suggest that the addition of anti-EGFR agents to chemotherapy is ineffective as first-line treatment for BRAFmt mCRC patients.

Abstract Disease progression after frontline therapy for Diffuse large B‐cell lymphoma (DLBCL) is a clinically significant event. Patients who experience early progression or have refractory disease have especially poor outcomes. Simple, clinically applicable prognostic tools are needed for selecting patients for consideration for novel therapies and prognostication in the relapsed/refractory (R/R) setting. Model building was performed in patients from the Surrogate endpoints in aggressive lymphoma (SEAL) consortium with disease progression after frontline immunochemotherapy. The primary endpoint was overall survival (OS) measured from date of progression. Validation was performed in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and Danish National Lymphoma Register (LYFO) cohorts. Model performance was assessed using time‐dependent concordance indices (c‐statistic) and calibration with metrics evaluated at 2 years from progression. Note, 1234 of 5112 patients treated with frontline immunochemotherapy in the SEAL consortium developed progressive disease. Time to progression on immunochemotherapy and age at progression were strongly associated with post‐progression OS (both p < 0.001). A prognostic model was developed incorporating spline fit for both variables. The model had good concordance in the discovery (0.67) and validation sets (LYFO c = 0.64, MER c = 0.68) with generally good calibration. Time to progression on frontline therapy is strongly associated with post‐progression OS in DLBCL. We developed and validated a simple to apply clinical prognostic tool in the R/R setting. The useful prediction of expected outcomes in R/R DLBCL and can inform treatment decisions such as considerations for CAR‐T therapy as well as trial designs. The model is available in smartphone‐based point of care applications.

377 Background: Neoadjuvant therapy has been associated with a median overall survival (OS) of 18 – 23 months (mo) in patients (pts) with BR pancreatic ductal adenocarcinoma (PDAC). To establish reference regimens to which novel treatments can be compared in future studies, we evaluated neoadjuvant mFOLFIRINOX with or without RT in BR PDAC in a phase II National Clinical Trials Network (NCTN) trial. Methods: Pts with ECOG PS 0-1 and BR PDAC confirmed by central real-time radiographic review after pre-registration were randomized to either arm A: 8 cycles of neoadjuvant mFOLFIRINOX (oxaliplatin 85 mg/m2, irinotecan 180 mg/m2, leucovorin 400 mg/m2 and infusional 5-fluorouracil 2400 mg/m2 over 46 hours), or arm B: 7 cycles of mFOLFIRINOX followed by stereotactic body RT (SBRT, 33-40 Gy in 5 fractions [fx]) or hypofractionated image guided RT (HIGRT, 25 Gy in 5 fx). Pts in either arm without disease progression underwent pancreatectomy, then 4 cycles of adjuvant mFOLFOX6 (oxaliplatin 85 mg/m2, leucovorin 400 mg/m2 and infusional 5-fluorouracil 2400 mg/m2 over 46 hours). The primary endpoint, 18-mo OS rate, of each arm was compared to a historical control of 50%. Planned interim analysis mandated closure of either arm in which <11 of first 30 accrued pts underwent R0 resection. Results: 155 pts pre-registered and 126 pts were enrolled to arm A (N=70; 54 randomized, 16 following closure of arm B) or arm B (N=56; closed at interim analysis, all pts randomized prior to closure). Median age (A: 63y, B: 67y), median CA 19-9 level (A: 171 U/ml, B: 248 U/ml) and ECOG PS (A: 51% PS 0, B: 57% PS 0) of registered pts were similar between arms (p > 0.05). Treatment detailed in Table. The 18-mo OS rate based on Kaplan Meier estimates was 67.9% (95%CI: 54.6 – 78.0) in arm A and 47.3% (95%CI: 33.7 – 59.7) in arm B. Among pts who underwent pancreatectomy, 18-mo OS rate was 93.1% (95%CI: 84.3 – 100) and 78.9% (95%CI: 62.6 – 99.6) in arm A and B, respectively. With median follow-up of 27 and 31 mo, median OS was 31.0 (95%CI: 22.2 – NE) mo and 17.1 (95%CI: 12.8 – 24.4) mo in arm A and B, respectively. Conclusions: Neoadjuvant mFOLFIRINOX was associated with favorable OS relative to historical data in pts with BL PDAC in this phase II NCTN trial. mFOLFIRINOX with hypofractionated RT did not improve OS compared to historical data. mFOLFIRINOX represents a reference regimen in this setting and a backbone on which to add novel agents. Support: U10CA180821, U10CA180882, U24CA196171; https://acknowledgments.alliancefound.org Clinical trial information: NCT02839343. [Table: see text]

343 Background: Alliance/CALGB 80802, a randomized phase III trial, evaluated sorafenib plus doxorubicin vs. doxorubicin in pts with HCC and showed no improvement in median overall survival (OS) (HR[95CI] 1.05[0.83-1.31]) or PFS (HR[95CI] 0.93[0.75-1.16]). In HCC surrogacy of tumor response with OS remains controversial, in part due to varying criteria used for response evaluation (e.g., RECIST1.1 and mRECIST). We evaluated the performance of several models to predict OS using pretreatment clinical and radiomic variables. Methods: In CALBG 80802, we segmented all measurable tumor lesions on sequential CT scans. A lesion’s imaging phenotype was deciphered with 23 uncorrelated quantitative imaging features measured at baseline and week (wk) 10 (first follow-up). An OS landmark survival analysis was conducted at wk 10. Patients were randomly assigned (3:1) to training (n = 92) and validation (n = 37) sets. In a training set, 6 random forest predictive models (6 signatures) used features that best predicted OS using 3 sets of variables: radiomics only (n = 23), clinical only (n = 9), radiomics and clinical (n = 32). Two time points (baseline only or baseline + wk 10) were assessed. Each signature's output was an individualized prediction and a continuous value ranging from 0 to 1 (from most to least favorable predicted OS). The primary endpoint was to compare these models' performance to predict OS using error rate (Harrell's concordance-index) in the validation set. Results: Of the 6 training signatures evaluated, the one achieving the highest performance in the validation set was an 8-feature signature combining radiomics and clinical variables measured at two time points (baseline + wk 10) with an error rate of 35.6%. The variables [rank of importance] (table) selected by the signature included baseline clinical features (albumin[1], AFP[2], Child-Pugh[4]), baseline radiomics features (component 17[3], component 1[5], component 9[7], tumor volume[8]) and wk 10 radiomics features (delta tumor volume[6]). Variable delta tumor volume [6] used a more enhanced estimation of tumor burden at baseline and a delta tumor volumetric measurement; compared to RECIST1.1 measurement of percentage change in unidimensional measurement of a subset of target lesions. The four quartiles of the signature were significantly associated with OS (Log-Rank, P < 0.0001). Conclusions: The selected combined radiomic and clinical composite signature provided the best prediction for OS in the 80802 study patients’ population. It is a suggested way forward to go beyond single anatomic measurement techniques such as RECIST or mRECIST. [Table: see text]

325 Background: Alliance/CALGB 80802 randomized phase III trial evaluated DO+S vs. S in pts with aHCC, and showed no improvement in median OS. Multi-drug resistant pathway mitigation by the Ras/Raf/MEK/ERK pathway and bFGF-mediated activation of Raf-1 promotes the formation of antiapoptotic Raf-1 and ASK1 complex, induced by anthracyclines. S efficiently blocks NS5A-recruited c-Raf mediated HCV replication and viral gene expression. Once inhibited by S, VEGF expression of HepG2 may limit HCV cellular entry. Release of Raf-1-Ask-1 dimer and inhibition of Raf-1 via S putatively differ in the presence or absence of DO. We hypothesize treatment with S reduces HCV titer levels (TL) and influence pts’ outcome. Methods: In 80802 HCV pts, TL were evaluated in both arms at baseline and post-baseline at Day 1 of Cycles 2, 3, and every 2 cycles and at progression or discontinuation of therapy. HCV undetectable (HCV-UN) levels were defined as < 50 copies/mL. TL were evaluated in relation to OS and PFS. HCV RNA levels were measured by TaqMan PCR and by genotype. Results: Of 356 pts, 83 were HCV+ with more Black/African American (25/50 = 50%) vs. White (54/239 = 23%) or other race groups (4/67 = 6%) (p < 0.0001). HCV titer data were available on 54 pts (S: 28, DO+S: 26). At baseline, 12 pts (S: 7, DO+S: 5) were HCV-UN, and post-baseline HCV TL did not significantly differ between treatment arms; one patient in each arm went from detectable (HCV-D) to HCV-UN. Post-baseline, 40 pts were HCV-D vs. 14 who were HCV-UN (S+DO: 8, S: 6 pts). Except for the two pts who became HCV-UN, baseline HCV-D vs. HCV-UN titers was similar to that status post-baseline. PFS and OS between HCV-D and HCV-UN both at baseline and post-baseline are delineated in the table. Conclusions: We observed that S did not influence HCV TL. Pts treated with DO+S vs. S had worse PFS if they had HCV-UN, and further that higher levels of HCV titers at baseline were associated with significantly improved PFS. Given the small sample size, these findings warrant further prospective evaluation. Support: U10CA180821, U10CA180882, U24CA196171; Bayer, Bristol-Myers-Squibb, and Sanofi. https://acknowledgments.alliancefound.org . Clinical trial information: NCT01015833. [Table: see text]

108 Background: Primary tumor sidedness has emerged as a prognostic and predictive biomarker for patients (pts) with metastatic colorectal cancer (mCRC). Tumor bulk has also been postulated to predict response to anti-EGFR therapy. We sought to evaluate the role of tumor bulk as a predictive biomarker to anti-EGFR therapy in pts with left- (LS) and right-sided (RS) mCRC. Methods: Data from 476 pts with mCRC enrolled across 2 first-line trials of anti-EGFR plus chemotherapy versus chemotherapy were pooled. Pts were included if there was available information on tumor sidedness and tumor bulk. All were KRAS wild-type and BRAF wild-type or unknown BRAF status. The right colon was defined as the cecum through the transverse colon, and the left colon as the splenic flexure through the rectum. Tumor bulk was the mean tumor size of target lesions at baseline, bulky defined as > 3.5 cm. Overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier and Cox models adjusting for performance status (PS), platelet count, primary tumor (PT) resection, number of metastatic sites, and stratified by study. Results: Pts with bulky tumors (211, 44%) had higher PS, white blood cell and platelet counts, higher CEA, fewer sites of metastatic disease, more liver than lung metastases, and fewer had PT resection. OS and PFS medians in months (mos) are presented in the table with 95% confidence intervals (95%CIs). Bulky tumors had inferior median OS compared with non-bulky (mOS, 17.9 vs. 21.3 mos, HRadj 1.33, 95% CI 1.05-1.69, P = 0.016) although median PFS was similar (mPFS, 8.6 vs. 8.7 mos, HRadj 1.15, 95% CI 0.92-1.42, P = 0.21). Conclusions: Tumor bulk is an independent prognostic factor for OS in KRAS wild-type and BRAF wild-type or unknown BRAF status pts. Pts with non-bulky RS tumors have survival outcomes similar to pts with bulky LS tumors. Although the mPFS for pts with RS tumors treated with anti-EGFR therapy was the lowest across subgroups, this finding was not statistically significant. Further research is warranted into whether pts with bulky RS tumors benefit from anti-EGFR therapy. Clinical trial information: NCT00182715, NCT00640081. [Table: see text]

10 Background: In colon cancer, tumor deposits (TD) have been associated with worse prognosis, but they are included in the TNM staging system only in the absence of lymph node metastasis (i.e., stage III pN1c tumors). Here we aimed at evaluating the prognostic value of TD and the impact of the addition of TD in the count of lymph node metastases in patients with stage III colon cancer from the CALGB/SWOG 80702 phase III trial (NCT01150045). Methods: Pathological reports of all patients were reviewed for the presence and the count of TD, primary tumor sidedness, lymphovascular invasion and perineural invasion. Cases without available pathological report or without specific information of TD were excluded. Prognostic associations were evaluated by multi-variable Cox models adjusting for treatment arm, T-stage, N-stage, lymphovascular invasion, perineural invasion and lymph node ratio. Results: Overall, 2028 patients were included, with 524 (26%) TD-positive and 1504 (74%) TD-negative stage III tumors. Of the TD-positive patients, 80 (15.4%) were node negative (i.e., pN1c), 239 (46.1%) were pN1a/b and 200 (38.55%) were pN2. 17.2% and 37.0% of all pN1a/b and pN2 tumors had TD. Overall median follow-up was 69.3 months. The presence of TD was associated with poorer DFS (adjusted hazard ratio (aHR) = 1.59, 95%CI 1.28-1.91) and OS (aHR = 1.52, 95%CI 1.18-1.95) in the overall population. The negative effect of TD on DFS and OS was observed for both pN1a/b and pN2 groups and confirmed in multivariate Cox model. Among TD-positive patients, the number of TD had a linear negative effect on DFS and OS. Adding TD to the count of lymph node metastases, 104 of 1570 (6.6%) patients initially considered as pN1 were re-staged as pN2. Re-staged pN2 patients experienced worse DFS (3-year DFS rate: 65.5% versus 80.3%, P = .0003) and OS (5-year OS rate: 69.1 versus 87.8%, P = .0005) than patients confirmed as pN1. Re-staged pN2 patients had similar DFS than patients initially staged as pN2 (3-year DFS rate: 65.5% versus 63.1%, P = .1992). OS curves of these 2 groups crossed, with better outcomes during the first 3 years of follow-up but poorer 5-year estimates for re-staged pN2 patients (5-year OS rate: 69.1% versus 74.8%, P = .0436). Conclusions: TD are found in more than one fourth of stage III colon cancer specimens. The number of TD has a linear deleterious effect on patients’ prognosis. Adding the number of TD to the count of lymph node metastases improves the prognostication accuracy of the TNM staging. Support: U10CA180821, U10CA180882; https://acknowledgments.alliancefound.org . Clinical trial information: NCT01150045.

PURPOSE: As oxaliplatin results in cumulative neurotoxicity, reducing treatment duration without loss of efficacy would benefit patients and healthcare providers. PATIENTS AND METHODS: Four of the six studies in the International Duration Evaluation of Adjuvant Chemotherapy (IDEA) collaboration included patients with high-risk stage II colon and rectal cancers. Patients were treated (clinician and/or patient choice) with either fluorouracil, leucovorin, and oxaliplatin (FOLFOX) or capecitabine and oxaliplatin (CAPOX) and randomly assigned to receive 3- or 6-month treatment. The primary end point is disease-free survival (DFS), and noninferiority of 3-month treatment was defined as a hazard ratio (HR) of < 1.2- v 6-month arm. To detect this with 80% power at a one-sided type one error rate of 0.10, a total of 542 DFS events were required. RESULTS: 3,273 eligible patients were randomly assigned to either 3- or 6-month treatment with 62% receiving CAPOX and 38% FOLFOX. There were 553 DFS events. Five-year DFS was 80.7% and 83.9% for 3-month and 6-month treatment, respectively (HR, 1.17; 80% CI, 1.05 to 1.31; P [for noninferiority] .39). This crossed the noninferiority limit of 1.2. As in the IDEA stage III analysis, the duration effect appeared dependent on the chemotherapy regimen although a test of interaction was negative. HR for CAPOX was 1.02 (80% CI, 0.88 to 1.17), and HR for FOLFOX was 1.41 (80% CI, 1.18 to 1.68). CONCLUSION: Although noninferiority has not been demonstrated in the overall population, the convenience, reduced toxicity, and cost of 3-month adjuvant CAPOX suggest it as a potential option for high-risk stage II colon cancer if oxaliplatin-based chemotherapy is suitable. The relative contribution of the factors used to define high-risk stage II disease needs better understanding.