Is cancer stage data missing completely at random? A report from a large population-based cohort of non-small cell lung cancer

IntroductionPopulation-based datasets are often used to estimate changes in utilization or outcomes of novel therapies. Inclusion or exclusion of unstaged patients may impact on interpretation of these studies.MethodsA large population-based dataset in Ontario, Canada of non-small cell lung cancer patients was examined to evaluate the characteristics and outcomes of unstaged patients compared to staged patients. Multivariable Poisson regression was used to evaluate differences in patient-level characteristics between groups. Kaplan-Meier estimates of survival and log-rank statistics were utilized.ResultsIn our Ontario cohort of 51,152 patients with NSCLC, 11.2% (n=5,707) were unstaged, and there was evidence that stage data was not missing completely at random. Those without assigned stage were more likely than staged patients to be older (RR [95%CI]), (70-79 vs. 20-59: 1.51 [1.38-1.66]; 80+ vs. 20-59: 2.87 [2.62-3.15]), have a higher comorbidity index (Score 1-2 vs 0: 1.19 [1.12-1.27]; 3 vs. 0: 1.49 [1.38-1.60]), and have a lower socioeconomic class (4 vs. 1 (lowest): 0.91 [0.84-0.98]; 5 vs. 1 (lowest): 0.89 [0.83-0.97]). Overall survival of unstaged patients suggested a mixture of early and advanced stage, but with a large proportion that are probably stage IV patients with more rapid death than those with reported stage IV disease.ConclusionIn this case study, evaluation of stage-specific health care utilization and outcomes for staged patients with stage IV disease at the population level may have a bias as a distinct subset of stage IV patients with rapid death are likely among those without a documented stage in administrative data

A perspective on life-cycle health technology assessment and real-world evidence for precision oncology in Canada

Health technology assessment (HTA) can be used to make healthcare systems more equitable and efficient. Advances in precision oncology are challenging conventional thinking about HTA. Precision oncology advances are rapid, involve small patient groups, and are frequently evaluated without a randomized comparison group. In light of these challenges, mechanisms to manage precision oncology uncertainties are critical. We propose a life-cycle HTA framework and outline supporting criteria to manage uncertainties based on real world data collected from learning healthcare systems. If appropriately designed, we argue that life-cycle HTA is the driver of real world evidence generation and furthers our understanding of comparative effectiveness and value. We conclude that life-cycle HTA deliberation processes must be embedded into healthcare systems for an agile response to the constantly changing landscape of precision oncology innovation. We encourage further research outlining the core requirements, infrastructure, and checklists needed to achieve the goal of learning healthcare supporting life-cycle HTA

Epigenetic modifier gene mutations in chronic myeloid leukemia (CML) at diagnosis are associated with risk of relapse upon treatment discontinuation

Non peer reviewe

Mortality due to cancer treatment delay: systematic review and meta-analysis.

OBJECTIVE: To quantify the association of cancer treatment delay and mortality for each four week increase in delay to inform cancer treatment pathways. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Published studies in Medline from 1 January 2000 to 10 April 2020. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Curative, neoadjuvant, and adjuvant indications for surgery, systemic treatment, or radiotherapy for cancers of the bladder, breast, colon, rectum, lung, cervix, and head and neck were included. The main outcome measure was the hazard ratio for overall survival for each four week delay for each indication. Delay was measured from diagnosis to first treatment, or from the completion of one treatment to the start of the next. The primary analysis only included high validity studies controlling for major prognostic factors. Hazard ratios were assumed to be log linear in relation to overall survival and were converted to an effect for each four week delay. Pooled effects were estimated using DerSimonian and Laird random effect models. RESULTS: The review included 34 studies for 17 indications (n=1 272 681 patients). No high validity data were found for five of the radiotherapy indications or for cervical cancer surgery. The association between delay and increased mortality was significant (P<0.05) for 13 of 17 indications. Surgery findings were consistent, with a mortality risk for each four week delay of 1.06-1.08 (eg, colectomy 1.06, 95% confidence interval 1.01 to 1.12; breast surgery 1.08, 1.03 to 1.13). Estimates for systemic treatment varied (hazard ratio range 1.01-1.28). Radiotherapy estimates were for radical radiotherapy for head and neck cancer (hazard ratio 1.09, 95% confidence interval 1.05 to 1.14), adjuvant radiotherapy after breast conserving surgery (0.98, 0.88 to 1.09), and cervix cancer adjuvant radiotherapy (1.23, 1.00 to 1.50). A sensitivity analysis of studies that had been excluded because of lack of information on comorbidities or functional status did not change the findings. CONCLUSIONS: Cancer treatment delay is a problem in health systems worldwide. The impact of delay on mortality can now be quantified for prioritisation and modelling. Even a four week delay of cancer treatment is associated with increased mortality across surgical, systemic treatment, and radiotherapy indications for seven cancers. Policies focused on minimising system level delays to cancer treatment initiation could improve population level survival outcomes

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Enhancer Remodeling during Adaptive Bypass to MEK Inhibition Is Attenuated by Pharmacologic Targeting of the P-TEFb Complex

Targeting the dysregulated BRaf-MEK-ERK pathway in cancer has increasingly emerged in clinical trial design. Despite clinical responses in specific cancers using inhibitors targeting BRaf and MEK, resistance develops often involving non-genomic adaptive bypass mechanisms. Inhibition of MEK1/2 by trametinib in triple negative breast cancer (TNBC) patients induced dramatic transcriptional responses, including upregulation of receptor tyrosine kinases (RTKs) comparing tumor samples before and after one week of treatment. In preclinical models MEK inhibition induced genome-wide enhancer formation involving the seeding of BRD4, MED1, H3K27 acetylation and p300 that drives transcriptional adaptation. Inhibition of P-TEFb associated proteins BRD4 and CBP/p300 arrested enhancer seeding and RTK upregulation. BRD4 bromodomain inhibitors overcame trametinib resistance, producing sustained growth inhibition in cells, xenografts and syngeneic mouse TNBC models. Pharmacological targeting of P-TEFb members in conjunction with MEK inhibition by trametinib is an effective strategy to durably inhibit epigenomic remodeling required for adaptive resistance

Genome-wide imputation identifies novel associations and localises signals in idiopathic inflammatory myopathies.

OBJECTIVES The idiopathic inflammatory myopathies (IIM) are heterogeneous diseases, thought to be initiated by immune activation in genetically predisposed individuals. In this study we imputed variants from the Immunochip array using a large reference panel to fine-map associations and identify novel associations in IIM. METHODS We analysed 2,565 Caucasian IIM samples collected through the Myositis Genetics Consortium (MYOGEN) and 10,260 ethnically-matched controls. We imputed 1,648,116 variants from the Immunochip array using the Haplotype Reference Consortium panel and conducted association analysis on IIM, and clinical and serological subgroups. RESULTS The human leukocyte antigen (HLA) locus was consistently the most significantly associated region. Four non-HLA regions reached genome-wide significance, three in the whole IIM cohort (SDK2 and LINC00924 - both novel, and STAT4), with evidence of independent variants in STAT4, and NAB1 in the polymyositis (PM) subgroup. We also found suggestive evidence of association with loci previously associated with other autoimmune rheumatic diseases (TEC and LTBR). We identified more significant associations than those previously reported in IIM, for STAT4 and DGKQ in the total cohort, for NAB1 and FAM167A-BLK loci in PM, and CCR5 in inclusion body myositis. We found enrichment of variants among DNase I hypersensitivity sites and histone marks associated with active transcription within blood cells. CONCLUSIONS We report novel and strong associations in IIM and PM, and localise signals to single genes and immune cell types. This article is protected by copyright. All rights reserved

Identification of Novel Associations and Localization of Signals in Idiopathic Inflammatory Myopathies Using Genome-Wide Imputation

OBJECTIVES: The idiopathic inflammatory myopathies (IIM) are heterogeneous diseases, thought to be initiated by immune activation in genetically predisposed individuals. In this study we imputed variants from the Immunochip array using a large reference panel to fine-map associations and identify novel associations in IIM. METHODS: We analysed 2,565 Caucasian IIM samples collected through the Myositis Genetics Consortium (MYOGEN) and 10,260 ethnically-matched controls. We imputed 1,648,116 variants from the Immunochip array using the Haplotype Reference Consortium panel and conducted association analysis on IIM, and clinical and serological subgroups. RESULTS: The human leukocyte antigen (HLA) locus was consistently the most significantly associated region. Four non-HLA regions reached genome-wide significance, three in the whole IIM cohort (SDK2 and LINC00924 - both novel, and STAT4), with evidence of independent variants in STAT4, and NAB1 in the polymyositis (PM) subgroup. We also found suggestive evidence of association with loci previously associated with other autoimmune rheumatic diseases (TEC and LTBR). We identified more significant associations than those previously reported in IIM, for STAT4 and DGKQ in the total cohort, for NAB1 and FAM167A-BLK loci in PM, and CCR5 in inclusion body myositis. We found enrichment of variants among DNase I hypersensitivity sites and histone marks associated with active transcription within blood cells. CONCLUSIONS: We report novel and strong associations in IIM and PM, and localise signals to single genes and immune cell types