Canadian cancer trials group LY.17: A randomized phase II study evaluating novel salvage therapy pre-autologous stem cell transplant in relapsed/refractory diffuse large B-cell lymphoma-outcome of rituximab-dose-intensive cyclophosphamide, etoposide, cisplatin (R-DICEP) versus R-GDP.

The Canadian Cancer Trials Group (CCTG) LY.17 is an ongoing multi-arm randomized phase II trial evaluating novel salvage therapies compared with R-GDP (rituximab, gemcitabine, dexamethasone and cisplatin) in autologous stem cell transplantation (ASCT)-eligible patients with relapsed/refractory diffuse large B-cell lymphoma (RR-DLBCL). This component of the LY.17 trial evaluated a dose-intensive chemotherapy approach using a single cycle of inpatient R-DICEP (rituximab, dose-intensive cyclophosphamide, etoposide and cisplatin) to achieve both lymphoma response and stem cell mobilization, shortening time to ASCT. This report is the result of the protocol-specified second interim analysis of the 67 patients who were randomized to either 1 cycle of R-DICEP or to 3 cycles of R-GDP. The overall response rate (ORR) was 65.6% for R-DICEP and 48.6% for R-GDP. The ASCT rate was 71.9% versus 54.3%, and 1-year progression-free survival rate was 42% versus 32%, respectively, for R-DICEP versus R-GDP. Although the improvement in ORR for R-DICEP versus R-GDP exceeded the pre-specified 10% threshold to proceed to full accrual of 64 patients/arm, higher rates of grade 3-5 toxicities, and the need for hospitalization led to the decision to stop this arm of the study. CCTG LY.17 will continue to evaluate different salvage regimens that incorporate novel agents.

deepAFT: A nonlinear accelerated failure time model with artificial neural network.

The Cox regression model or accelerated failure time regression models are often used for describing the relationship between survival outcomes and potential explanatory variables. These models assume the studied covariates are connected to the survival time or its distribution or their transformations through a function of a linear regression form. In this article, we propose nonparametric, nonlinear algorithms (deepAFT methods) based on deep artificial neural networks to model survival outcome data in the broad distribution family of accelerated failure time models. The proposed methods predict survival outcomes directly and tackle the problem of censoring via an imputation algorithm as well as re-weighting and transformation techniques based on the inverse probabilities of censoring. Through extensive simulation studies, we confirm that the proposed deepAFT methods achieve accurate predictions. They outperform the existing regression models in prediction accuracy, while being flexible and robust in modeling covariate effects of various nonlinear forms. Their prediction performance is comparable to other established deep learning methods such as deepSurv and random survival forest methods. Even though the direct output is the expected survival time, the proposed AFT methods also provide predictions for distributional functions such as the cumulative hazard and survival functions without additional learning efforts. For situations where the popular Cox regression model may not be appropriate, the deepAFT methods provide useful and effective alternatives, as shown in simulations, and demonstrated in applications to a lymphoma clinical trial study.

Contact Days Associated With Cancer Treatments in the CCTG LY.12 Trial.

BACKGROUND: When cancer treatments have similar oncologic outcomes, the number of days with in-person healthcare contact (""contact days'') can help contextualize expected time use with each treatment. We assessed contact days in a completed randomized clinical trial. PATIENTS AND METHODS: We conducted a secondary analysis of the CCTG LY.12 RCT that evaluated 2-3 cycles of gemcitabine, dexamethasone, and cisplatin (GDP) vs. dexamethasone, cytarabine, and cisplatin (DHAP) in 619 patients with relapsed/refractory lymphoma prior to stem cell transplant. Primary analyses reported similar response rates and survival. We calculated patient-level "contact days" by analyzing trial forms. The study period was from assignment to progression or transplant. Days without healthcare contact were considered "home days''. We compared measures of contact days across arms. RESULTS: The study period was longer in the GDP arm (median 50, vs. 47 days, P = .007). Contact days were comparable in both arms (median 18 vs 19, P = 0.79), but home days were higher in the GDP arm (median 33 vs 28, P < .001). The proportion of contact days was lower in the GDP arm (34%, vs. 38%, P = .009). The GDP arm experienced more contact days related to planned outpatient chemotherapy (median, 10 vs. 8 days), but the DHAP arm experienced many more inpatient contact days (median, 11 vs. 0 days). CONCLUSIONS: Measures of time use, such as contact days, can be extracted from RCTs. In LY.12, despite comparable oncologic outcomes, GDP was associated with fewer contact days. Such information can guide decision-making for patients with hematological cancers, who already face significant healthcare contact.

Metformin, placebo, and endocrine therapy discontinuation among participants in a randomized double-blind trial of metformin vs placebo in hormone receptor-positive early-stage breast cancer (CCTG MA32).

BACKGROUND: The MA32 study investigated whether 5 years of metformin (versus placebo) improves invasive disease-free survival in early-stage breast cancer (BC). Non-adherence to endocrine therapy (ET) and medications for chronic conditions is common and increases with drug toxicity and polypharmacy. This secondary analysis evaluates rates and predictors of early discontinuation of metformin, placebo, and ET among participants with HR-positive BC. METHODS: Patients with high-risk non-metastatic BC were randomized to 60 months of metformin (850 mg BID) or placebo BID. Patients were administered bottles of metformin/placebo every 180 days. Metformin/placebo adherence was defined as a bottle dispensed at month 48 or later. The ET adherence analysis included patients with HR-positive BC who received ET with start and stop date reported, with adherence defined as > 48 months of use. Associations of covariates with study drug and ET adherence were examined using multivariable models. RESULTS: Among the 2521 HR-positive BC patients, 32.9% were non-adherent to study drug. Non-adherence was higher among patients on metformin vs placebo (37.1% vs 28.7%, p < 0.001). Reassuringly, ET discontinuation rates were similar between treatment arms (28.4% vs 28.0%, p = 0.86). Patients who were non-adherent to ET were more likely to discontinue study therapy (38.8% vs 30.1%, p < 0.0001). In a multivariable analysis, study drug non-adherence was increased with metformin vs placebo (OR: 1.50, 95% CI 1.25-1.80; p < 0.0001); non-adherence to ET (OR: 1.47, 95% CI 1.20-1.79, p < 0.0001); grade 1 or greater GI toxicity during the first 2 years; lower age; and higher body mass index. CONCLUSION: While non-adherence was higher among patients on metformin, it was still considerable among patients on placebo. Reassuringly, treatment arm allocation did not impact ET adherence. Attention to global medication adherence is needed to improve BC and non-oncological outcomes in cancer survivors. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01.

A nonparametric simultaneous confidence band for biomarker effect on the restricted mean survival time.

Study of prognostic and predictive biomarkers plays an important role in the design and analysis of clinical trials. The Cox proportional hazards model is often used to study the biomarker main effect and the treatment-biomarker interaction effect for survival data. The estimated effects can be biased if the proportional hazards assumption is violated. The restricted mean survival time is becoming popular in clinical studies for having a clear intuitive interpretation. In this article, we first propose nonparametric methods to make statistical inference for the one-sample problem of the biomarker effect on the restricted mean survival time; we then extend the methods to the two-sample problem for studying the difference in the biomarker effects between treatment groups in clinical trials. For a given biomarker, the restricted mean survival time is estimated by kernel smoothing methods with the inverse probability of censoring weights. We prove the consistency for the estimates and develop simultaneous confidence bands for the biomarker effects on the restricted mean survival time. The simultaneous confidence bands are evaluated in extensive simulation studies and are found to have good finite sample performance. We then apply the proposed methods to a breast cancer study conducted by the Breast International Group (BIG) to illustrate how the Ki67 biomarker, a protein marker of cell proliferation, affects the survival time of patients, compared between the treatment groups.

Power and sample size calculation for incremental net benefit in cost effectiveness analyses with applications to trials conducted by the Canadian Cancer Trials Group.

BACKGROUND: Historically, a priori power and sample size calculations have not been routinely performed cost-effectiveness analyses (CEA), partly because the absence of published cost and effectiveness correlation and variance data, which are essential for power and sample size calculations. Importantly, the empirical correlation between cost and effectiveness has not been examined with respect to the estimation of value-for-money in clinical literature. Therefore, it is not well established if cost-effectiveness studies embedded within randomized-controlled-trials (RCTs) are under- or over-powered to detect changes in value-for-money. However, recently guidelines (such as those from ISPOR) and funding agencies have suggested sample size and power calculations should be considered in CEAs embedded in clinical trials. METHODS: We examined all RCTs conducted by the Canadian Cancer Trials Group with an embedded cost-effectiveness analysis. Variance and correlation of effectiveness and costs were derived from original-trial data. The incremental net benefit method was used to calculate the power of the cost-effectiveness analysis, with exploration of alternative correlation and willingness-to-pay values. RESULTS: We identified four trials for inclusion. We observed that a hypothetical scenario of correlation coefficient of zero between cost and effectiveness led to a conservative estimate of sample size. The cost-effectiveness analysis was under-powered to detect changes in value-for-money in two trials, at willingness-to-pay of $100,000. Based on our observations, we present six considerations for future economic evaluations, and an online program to help analysts include a priori sample size and power calculations in future clinical trials. CONCLUSION: The correlation between cost and effectiveness had a potentially meaningful impact on the power and variance of value-for-money estimates in the examined cost-effectiveness analyses. Therefore, the six considerations and online program, may facilitate a priori power calculations in embedded cost-effectiveness analyses in future clinical trials.

Health-related quality of life in early-stage Hodgkin lymphoma: a longitudinal analysis of the ABVD arm in the randomized controlled trial HD.6.

Early-stage Hodgkin lymphoma has become one of the most curable hematologic malignancies. Depending upon the disease location, possible toxicities, and patient preference, chemotherapy alone with ABVD remains an accepted treatment modality for this disease. There remains a paucity of data regarding the longitudinal trajectory of health-related quality of life (HRQoL) in patients treated for HL. The impact of disease and treatment on HRQoL is increasingly important to understand as the number of long-term survivors increases. We report the longitudinal HRQoL using data prospectively collected from diagnosis up to 10 years post-treatment in the ABVD arm of the HD.6 randomized controlled trial for early-stage HL patients (N=169). We analyzed HRQoL using the EORTC QLQ-C30 collected at baseline, 3 months, 6 months, and 12 months after completion of chemotherapy and yearly up to year 10. Clinically and statistically significant improvements were noted for specific domains including emotional (3 months post-treatment), social (12 months post-treatment) and financial functioning (2 years post-treatment), and the specific symptom of fatigue (6 months post-treatment) during the follow-up period. To our knowledge, this is the first prospective, longitudinal analysis of HRQoL specifically among patients with early-stage HL treated with ABVD therapy alone. Although improvements were noted, sustained clinically and statistically significant improvements were noted only in select symptoms emphasizing the need to better understand and optimize HRQoL among this patient group.

Real-world colorectal cancer diagnostic pathways in Ontario, Canada: A population-based study.

OBJECTIVE: This study aimed to identify colorectal cancer (CRC) diagnostic pathways and describe patients in those pathway groups. METHODS: This was a cross-sectional study of CRC patients in Ontario, Canada, diagnosed 2009-2012 that used linked administrative data at ICES. We used cluster analysis on 11 pathway variables characterising patient presentation, symptoms, procedures and referrals. We assessed associations between patient- and disease-related characteristics and diagnostic pathway group. We further characterised the pathways by diagnostic interval and number of related physician visits. RESULTS: Six diagnostic pathways were identified, with three adhering to provincial diagnostic guidelines: screening (N = 4494), colonoscopy (N = 10,066) and imaging plus colonoscopy (N = 3427). Non-adherent pathways were imaging alone (N = 2238), imaging and emergency presentation (N = 2849) and no pre-diagnostic workup (N = 887). Patients in adherent pathways were younger, had fewer comorbidities, lived in less deprived areas and had earlier stage disease. The median diagnostic interval length varied across pathways from 12 to 126 days, correlating with the number of CRC-related visits. CONCLUSIONS: This study demonstrated substantial variations in real-world CRC diagnostic pathways and 25% were diagnosed through non-adherent pathways. Those patients were older, had more comorbid disease and had higher stage cancer. Further research needs to identify and describe the reasons for divergent diagnostic processes.

Effect of Metformin vs Placebo on Invasive Disease-Free Survival in Patients With Breast Cancer: The MA.32 Randomized Clinical Trial.

Importance: Metformin, a biguanide commonly used to treat type 2 diabetes, has been associated with potential beneficial effects across breast cancer subtypes in observational and preclinical studies. Objective: To determine whether the administration of adjuvant metformin (vs placebo) to patients with breast cancer without diabetes improves outcomes. Design, Setting, and Participants: MA.32, a phase 3 randomized, placebo-controlled, double-blind trial, conducted in Canada, Switzerland, US, and UK, enrolled 3649 patients with high-risk nonmetastatic breast cancer receiving standard therapy between August 2010 and March 2013, with follow-up to October 2020. Interventions: Patients were randomized (stratified for hormone receptor [estrogen receptor and/or progesterone receptor {ER/PgR}] status, positive vs negative; body mass index, ≤30 vs >30; human epidermal growth factor receptor 2 [ERBB2, formerly HER2 or HER2/neu], positive vs negative; and any vs no chemotherapy) to 850 mg of oral metformin twice a day (n = 1824) or oral placebo twice a day (n = 1825) for 5 years. Main Outcomes and Measures: The primary outcome was invasive disease-free survival in hormone receptor-positive breast cancer. Of the 8 secondary outcomes, overall survival, distant relapse-free survival, and breast cancer-free interval were analyzed. Results: Of the 3649 randomized patients (mean age, 52.4 years; 3643 women [99.8%]), all (100%) were included in analyses. After a second interim analysis, futility was declared for patients who were ER/PgR-, so the primary analysis was conducted for 2533 patients who were ER/PgR+. The median duration of follow-up in the ER/PgR+ group was 96.2 months (range, 0.2-121 months). Invasive disease-free survival events occurred in 465 patients who were ER/PgR+. The incidence rates for invasive disease-free survival events were 2.78 per 100 patient-years in the metformin group vs 2.74 per 100 patient-years in the placebo group (hazard ratio [HR], 1.01; 95% CI, 0.84-1.21; P = .93), and the incidence rates for death were 1.46 per 100 patient-years in the metformin group vs 1.32 per 100 patient-years in the placebo group (HR, 1.10; 95% CI, 0.86-1.41; P = .47). Among patients who were ER/PgR-, followed up for a median of 94.1 months, incidence of invasive disease-free survival events was 3.58 vs 3.60 per 100 patient-years, respectively (HR, 1.01; 95% CI, 0.79-1.30; P = .92). None of the 3 secondary outcomes analyzed in the ER/PgR+ group had statistically significant differences. Grade 3 nonhematological toxic events occurred more frequently in patients taking metformin than in patients taking placebo (21.5% vs 17.5%, respectively, P = .003). The most common grade 3 or higher adverse events in the metformin vs placebo groups were hypertension (2.4% vs 1.9%), irregular menses (1.5% vs 1.4%), and diarrhea (1.9% vs 7.0%). Conclusions and Relevance: Among patients with high-risk operable breast cancer without diabetes, the addition of metformin vs placebo to standard breast cancer treatment did not significantly improve invasive disease-free survival. Trial Registration: ClinicalTrials.gov Identifier: NCT01101438.

A descriptive cost-analysis of MYX.1/MCRN003, a phase 2 clinical trial evaluating high-dose weekly carfilzomib, cyclophosphamide, and dexamethasone in relapsed and refractory multiple myeloma.

BACKGROUND: The prevalence of multiple myeloma is increasing and there is a need to evaluate escalating therapy costs (Canadian Cancer Statistics A, 2020). The MYX.1 phase II trial showed that high-dose weekly carfilzomib, cyclophosphamide, and dexamethasone (wKCD) is efficacious in relapsed and refractory disease. We conducted a descriptive cost analysis, from the perspective of the Canadian public healthcare system, using trial data. METHODS: The primary outcome was the mean total cost per patient. Resource utilization data were collected from all 75 trial patients over a trial time horizon. Costs are presented in Canadian dollars (2020). RESULTS: The cost of treatment was calculated from the time of patient (pt) enrollment until the second data lock. The mean total cost was $203 336.08/pt (range $17 891.27-$505 583.55) Canadian dollars (CAD, where 1 CAD = 0.67 Euro (EUR)) and $14 081.45/pt per cycle. The median number of cycles was 15. The predominant cost driver was the cost of chemotherapy accounting for an average of $179 332.78/pt or $12 419.17/pt per cycle. Carfilzomib acquisition accounted for the majority of chemotherapy costs - $162 471.65/pt or $11 251.50/pt per cycle. Fifty-six percent (56%) of patients had at least one hospitalization during the trial period with an average cost of $12 657.86 per hospitalization. Three patients developed thrombotic microangiopathy (TMA) with an average cost of $18 863.32/pt including the cost of hospitalizations and therapeutic plasma exchange. CONCLUSIONS: High-dose wKCD is an active triplet regimen for relapsed and refractory multiple myeloma (RRMM) associated with reduced total cost compared with twice-weekly carfilzomib-based regimens.

Weekly carfilzomib plus cyclophosphamide and dexamethasone in the treatment of relapsed/refractory multiple myeloma: Final results from the MCRN-003/MYX.1 single arm phase II trial.

The MCRN-003/CCTGMYX.1 is a single arm phase II trial of weekly carfilzomib, cyclophosphamide and dexamethasone (wKCd), exploring a convenient immunomodulator (IMiD)-free regimen in relapsed myeloma. Weekly carfilzomib (20/70 mg/m2 ), dexamethasone 40 mg and cyclophosphamide 300 mg/m2 was delivered over 28-day cycles. The primary endpoint was overall response after four cycles. Secondary endpoints included toxicity, response depth, PFS and OS. Exploratory endpoints included the impact of cytogenetics, prior therapy exposure and serum free light chain (sFLC) escape; 76 patients were accrued. The ORR was 85% (68% ≥very good partial response [VGPR] and 29% ≥complete response [CR]). The median OS and PFS were 27 and 17 months respectively. High-risk cytogenetics conferred a worse ORR (75% vs. 97%, p = .013) and median OS (18 months vs. NR, p = .002) with a trend toward a worse median PFS (14 vs. 22 months, p = .06). Prior proteasome inhibitor (PI) or lenalidomide did not influence OS or PFS. The sFLC was noted in 15% of patients with a median PFS of 17 months when included as a progression event. The most common ≥ grade 3 non-hematologic adverse events were infectious (40%), vascular (17%) and cardiac (15%). The wKCD is a safe and effective regimen in relapse, especially for patients ineligible for lenalidomide-based therapies.

Minimization of resource utilization data collected within cost-effectiveness analyses conducted alongside Canadian Cancer Trials Group phase III trials.

BACKGROUND: Cost-effectiveness analyses embedded within randomized trials allow for evaluation of value alongside conventional efficacy outcomes; however, collection of resource utilization data can require considerable trial resources. METHODS: We re-analyzed the results from four phase III Canadian Cancer Trials Group trials that embedded cost-effectiveness analyses to determine the impact of minimizing potential cost categories on the incremental cost-effectiveness ratios. For each trial, we disaggregated total costs into component incremental cost categories and recalculated incremental cost-effectiveness ratios using (1) only the top 3 cost categories, (2) the top 5 cost categories, and (3) all cost components. Using individual trial-level data, confidence intervals for each incremental cost-effectiveness ratio simulation were generated by bootstrapping and descriptively presented with the original confidence intervals (and incremental cost-effectiveness ratios) from the publications. RESULTS: Drug acquisition costs represented the highest incremental cost category in three trials, while hospitalization costs represented the other consistent cost driver and the top incremental cost category in the fourth trial. Recalculated incremental cost-effectiveness ratios based on fewer cost components (top 3 and top 5) did not differ meaningfully from the original published results. Based on conventional willingness-to-pay thresholds (US$50,000-US$100,000 per quality-adjusted life-year), none of the re-analyses would have changed the original perception of whether the experimental therapies were considered cost-effective. CONCLUSIONS: These results suggest that the collection of resource utilization data within cancer trials could be narrowed. Omission of certain cost categories that have minimal impact on incremental cost-effectiveness ratio, such as routine laboratory investigations, could reduce the costs and undue burden associated with the collection of data required for cancer trial cost-effectiveness analyses.

Higher serum PD-L1 level predicts increased overall survival with lapatinib versus trastuzumab in the CCTG MA.31 phase 3 trial.

BACKGROUND: The purpose of this retrospective biomarker study of the Canadian Cancer Trials Group (CCTG) MA.31 randomized phase 3 trial (lapatinib vs trastuzumab) of HER2-positive metastatic breast cancer (MBC) was to evaluate the prognostic and predictive biomarker utility of pretreatment serum programmed death ligand 1 (PD-L1) levels. METHODS: CCTG MA.31 accrued 652 HER2-positive patients; 387 had serum available (185 in the trastuzumab arm and 202 in the lapatinib arm). The Ella immunoassay platform (ProteinSimple, San Jose, California) was used to quantitate serum PD-L1 levels. Stepwise forward Cox multivariable analyses were performed for progression-free survival and overall survival (OS). RESULTS: In the whole trial population, continuous pretreatment serum PD-L1 levels were not associated with OS. However, within the trastuzumab arm, a higher continuous pretreatment serum PD-L1 level was significant for shorter OS (hazard ratio [HR], 3.85; P = .04), but within the lapatinib arm, pretreatment serum PD-L1 was not associated with OS (P = .37). In the whole trial, in a multivariable analysis for OS, serum PD-L1 (median cut point) remained a significant independent covariate (HR, 2.38; P = .001). There was a significant interaction between treatment arm and continuous serum PD-L1 (bootstrap method; P = .0025): at or above 214.2 pg/mL (the 89th percentile), serum PD-L1 was associated with significantly shorter OS with trastuzumab treatment versus lapatinib treatment. CONCLUSIONS: In the CCTG MA.31 trial, serum PD-L1 was a significant predictive factor: a higher pretreatment serum PD-L1 level was associated with shorter OS with trastuzumab treatment but with longer OS with lapatinib treatment. Immune evasion may decrease the effectiveness of trastuzumab therapy. Further evaluation of elevated serum PD-L1 in advanced breast cancer is warranted to identify patients with HER2-positive MBC who may benefit from novel immune-targeted therapies in addition to trastuzumab.

Joint modeling of binary response and survival for clustered data in clinical trials.

In clinical trials, it is often desirable to evaluate the effect of a prognostic factor such as a marker response on a survival outcome. However, the marker response and survival outcome are usually associated with some potentially unobservable factors. In this case, the conventional statistical methods that model these two outcomes separately may not be appropriate. In this paper, we propose a joint model for marker response and survival outcomes for clustered data, providing efficient statistical inference by considering these two outcomes simultaneously. We focus on a special type of marker response: a binary outcome, which is investigated together with survival data using a cluster-specific multivariate random effect variable. A multivariate penalized likelihood method is developed to make statistical inference for the joint model. However, the standard errors obtained from the penalized likelihood method are usually underestimated. This issue is addressed using a jackknife resampling method to obtain a consistent estimate of standard errors. We conduct extensive simulation studies to assess the finite sample performance of the proposed joint model and inference methods in different scenarios. The simulation studies show that the proposed joint model has excellent finite sample properties compared to the separate models when there exists an underlying association between the marker response and survival data. Finally, we apply the proposed method to a symptom control study conducted by Canadian Cancer Trials Group to explore the prognostic effect of covariates on pain control and overall survival.

A hierarchical testing approach for detecting safety signals in clinical trials.

Detecting safety signals in clinical trial safety data is known to be challenging due to high dimensionality, rare occurrence, weak signal, and complex dependence. We propose a new hierarchical testing approach for analyzing safety data from a typical randomized clinical trial. This approach accounts for the hierarchical structure of adverse events (AEs), that is, AEs are categorized by system organ class (SOC). Our approach contains two steps: the first step tests, for each SOC, whether any AEs within this SOC are differently distributed between treatment arms; and the second step identifies signal AEs from SOCs passing the first step tests. We show the superiority, in terms of power of detecting safety signals given controlled false discovery rate, of the new approach comparing with currently available approaches through simulation studies. We also demonstrate this approach with two real data examples.

Deep sequencing across germline genome-wide association study signals relating to breast cancer events in women receiving aromatase inhibitors for adjuvant therapy of early breast cancer.

OBJECTIVE: To identify additional genetic variants beyond those observed in a previous genome-wide association study (GWAS) in women treated on the MA.27 clinical trial in which women were randomized to 5 years of adjuvant therapy with anastrozole or exemestane. PATIENTS AND METHODS: We performed a matched case-control study in 234 women who had a recurrence of breast cancer (cases) and 649 women who had not (controls). The analysis was restricted to White women with an estrogen receptor-positive breast cancer. Multiplex PCR-based targeted deep sequencing was performed of the MIR2052HG region on chromosome 8 between positions 75.4 and 75.7, a span of 300 kb, in an attempt to identify additional functional single nucleotide polymorphisms (SNPs). RESULTS: A total of 4677 unique variants were identified that had not been identified in the previous GWAS. Clinical Annotation of Variants analysis revealed 10 variants, including eight SNPs and two insertion-deletion mutations with moderate or high impact. However, none of the common and variant regions was significant after adjustment for the most significant SNP (rs13260300) identified in our previous GWAS. We performed haplotype analysis that revealed two regions in which the haplotypes lost significance when adjusted for this prior GWAS SNP and one region with two significant haplotypes (P = 0.046 and 0.031) after adjusting for the GWAS SNP. CONCLUSION: We were unable to identify common or rare variant regions that added value to the findings from our previous GWAS. We did find two haplotypes that were significant after adjusting for our top GWAS SNP but these were considered to be of marginal value.

Advantages of the net benefit regression framework for trial-based economic evaluations of cancer treatments: an example from the Canadian Cancer Trials Group CO.17 trial.

BACKGROUND: Economic evaluations commonly accompany trials of new treatments or interventions; however, regression methods and their corresponding advantages for the analysis of cost-effectiveness data are not widely appreciated. METHODS: To illustrate regression-based economic evaluation, we review a cost-effectiveness analysis conducted by the Canadian Cancer Trials Group's Committee on Economic Analysis and implement net benefit regression. RESULTS: Net benefit regression offers a simple option for cost-effectiveness analyses of person-level data. By placing economic evaluation in a regression framework, regression-based techniques can facilitate the analysis and provide simple solutions to commonly encountered challenges (e.g., the need to adjust for potential confounders, identify key patient subgroups, and/or summarize "challenging" findings, like when a more effective regimen has the potential to be cost-saving). CONCLUSIONS: Economic evaluations of patient-level data (e.g., from a clinical trial) can use net benefit regression to facilitate analysis and enhance results.

Regional Nodal Irradiation in Early-Stage Breast Cancer.

BACKGROUND: Most women with breast cancer who undergo breast-conserving surgery receive whole-breast irradiation. We examined whether the addition of regional nodal irradiation to whole-breast irradiation improved outcomes. METHODS: We randomly assigned women with node-positive or high-risk node-negative breast cancer who were treated with breast-conserving surgery and adjuvant systemic therapy to undergo either whole-breast irradiation plus regional nodal irradiation (including internal mammary, supraclavicular, and axillary lymph nodes) (nodal-irradiation group) or whole-breast irradiation alone (control group). The primary outcome was overall survival. Secondary outcomes were disease-free survival, isolated locoregional disease-free survival, and distant disease-free survival. RESULTS: Between March 2000 and February 2007, a total of 1832 women were assigned to the nodal-irradiation group or the control group (916 women in each group). The median follow-up was 9.5 years. At the 10-year follow-up, there was no significant between-group difference in survival, with a rate of 82.8% in the nodal-irradiation group and 81.8% in the control group (hazard ratio, 0.91; 95% confidence interval [CI], 0.72 to 1.13; P=0.38). The rates of disease-free survival were 82.0% in the nodal-irradiation group and 77.0% in the control group (hazard ratio, 0.76; 95% CI, 0.61 to 0.94; P=0.01). Patients in the nodal-irradiation group had higher rates of grade 2 or greater acute pneumonitis (1.2% vs. 0.2%, P=0.01) and lymphedema (8.4% vs. 4.5%, P=0.001). CONCLUSIONS: Among women with node-positive or high-risk node-negative breast cancer, the addition of regional nodal irradiation to whole-breast irradiation did not improve overall survival but reduced the rate of breast-cancer recurrence. (Funded by the Canadian Cancer Society Research Institute and others; MA.20 ClinicalTrials.gov number, NCT00005957.).

A bioclinical prognostic model using MYC and BCL2 predicts outcome in relapsed/refractory diffuse large B-cell lymphoma.

The objective of this study was to create a bioclinical model, based on clinical and molecular predictors of event-free and overall survival for relapsed/refractory diffuse large B-cell lymphoma patients treated on the Canadian Cancer Trials Group (CCTG) LY12 prospective study. In 91 cases, sufficient histologic material was available to create tissue microarrays and perform immunohistochemistry staining for CD10, BCL6, MUM1/IRF4, FOXP1, LMO2, BCL2, MYC, P53 and phosphoSTAT3 (pySTAT3) expression. Sixty-seven cases had material sufficient for fluorescent in situ hybridization (FISH) for MYC and BCL2 In addition, 97 formalin-fixed, paraffin-embedded tissue samples underwent digital gene expression profiling (GEP) to evaluate BCL2, MYC, P53, and STAT3 expression, and to determine cell-of-origin (COO) using the Lymph2Cx assay. No method of determining COO predicted event-free survival (EFS) or overall survival (OS). Factors independently associated with survival outcomes in multivariate analysis included primary refractory disease, elevated serum lactate dehydrogenase (LDH) at relapse, and MYC or BCL2 protein or gene expression. A bioclinical score using these four factors predicted outcome with 3-year EFS for cases with 0-1 vs 2-4 factors of 55% vs 16% (P<0.0001), respectively, assessing MYC and BCL2 by immunohistochemistry, 46% vs. 5% (P<0.0001) assessing MYC and BCL2 messenger ribonucleic acid (mRNA) by digital gene expression, and 42% vs 21% (P=0.079) assessing MYC and BCL2 by FISH. This proposed bioclinical model should be further studied and validated in other datasets, but may discriminate relapsed/refractory diffuse large B-cell lymphoma (DLBCL) patients who could benefit from conventional salvage therapy from others who require novel approaches. The LY12 study; clinicaltrials.gov Identifier: 00078949.

Impact of Physician Navigators on productivity indicators in the ED.

OBJECTIVES: We created Physician Navigators in our ED to help improve emergency physician (EP) productivity. We aimed to quantify the effect of Physician Navigators on measures of EP productivity: patient seen per hour (Pt/hr), and turn-around time (TAT) to discharge. Secondary objectives included examining their impact on measures of ED throughput for non-resuscitative patients: ED length of stay (LOS), door-to-physician time and left-without-being-seen rates (LWBS). METHODS: In this retrospective study, 6845 clinical shifts worked by 20 EPs at a community ED in Newmarket, Canada from 1 January 2012 to 31 March 2015 were evaluated. Using a clustered design, we compared productivity measures between shifts with and without Physician Navigators, by physician. We used a linear mixed model to examine mean changes in Pt/hr and TAT to discharge for EPs who employed Physician Navigators. For secondary objectives, autoregressive modelling was performed to compare ED throughput metrics before and after the implementation of Physician Navigators for non-resuscitative patients. RESULTS: Patient volumes increased by 20 patients per day (p<0.001). Mean Pt/hr increased by 1.07 patients per hour (0.98 to 1.16, p<0.001). The mean TAT to discharge decreased by 10.6 min (-13.2 to -8.0, p<0.001). After implementation of the Physician Navigator programme, overall mean LOS for non-resuscitative patients decreased by 2.6 min (p=0.007), and mean door-to-physician time decreased by 7.4 min (p<0.001). LBWS rates decreased from 1.13% to 0.63% of daily patient volume (p<0.001). CONCLUSION: Despite an ED volume increase, the use of a Physician Navigator was associated with significant improvements in EP productivity, and significant reductions in ED throughput times.