The association of delay in curative intent treatment with survival among breast cancer patients: findings from the Women's Health Initiative.

PURPOSE: Delays in adjuvant breast cancer (BC) therapy have been shown to worsen outcomes. However, thus far studies have only evaluated delays to initial treatment, or a particular modality, such as chemotherapy, leaving uncertainty about the role of delay to subsequent therapy and the effects of cumulative delay, on outcomes. We investigated the associations of delays across treatment modalities with survival. METHODS: We included 3368 women with incident stage I-III BC in the Women's Health Initiative (WHI) enrolled in fee-for-service Medicare who underwent definitive surgery. This prospective analysis characterized treatment delays by linking WHI study records to Medicare claims. Delays were defined as > 8 weeks to surgery, chemotherapy, and radiation from diagnosis or prior treatment. We used Cox proportional hazards models to estimate BC-specific mortality (BCSM) and all-cause mortality (ACM) in relation to treatment delays. RESULTS: We found 21.8% of women experienced delay to at least one therapy modality. In adjusted analysis, delay to chemotherapy was associated with a higher risk of BCSM (HR = 1.71; 95% CI 1.07-2.75) and ACM (HR = 1.39; 95% CI 1.02-1.90); delay in radiation increased BCSM risk (HR = 1.49; 95% CI 1.00-2.21) but not ACM risk (HR = 1.19; 95% CI 0.99-1.42). Delays across multiple treatment modalities increased BCSM risk threefold (95% CI 1.51-6.12) and ACM risk 2.3-fold (95% CI 1.50-3.50). CONCLUSIONS: A delay to a single treatment modality and delay to a greater extent an accumulation of delays were associated with higher BCSM and ACM after BC. Timely care throughout the continuum of breast cancer treatment is important for optimal outcomes.

The incidence of thromboembolism for lenalidomide versus thalidomide in older patients with newly diagnosed multiple myeloma.

It is uncertain if different immunomodulatory drugs (IMID) pose distinct thrombotic risk in patients with newly diagnosed multiple myeloma (MM). Among 2397 MM patients from the SEER-Medicare database from 2007 to 2013, 78% received lenalidomide, and 22% received thalidomide. After inverse probability weighting to balance confounders, the 12-month incidences of venous thromboembolism (VTE 10%) and arterial thromboembolism (ATE 5%) were similarly high in both groups. Lenalidomide versus thalidomide had a subdistribution hazard ratio of 1.11 (0.59-2.02) for VTE and a subdistribution hazard ratio of 0.96 (0.45-1.98) for ATE. Overall survival was not significantly different with a hazard ratio of 0.88 (0.60-1.18) for lenalidomide versus thalidomide. Concurrent anticoagulant prophylaxis was infrequently prescribed in < 20% of both groups. Our study demonstrates that despite improvement in myeloma-directed therapy and supportive care, thrombosis remains an important consideration for all IMID-treated MM patients. Appropriate risk stratification and vigilant thromboprophylaxis remain essential to prevent this complication.

Derivation and Validation of a Risk Assessment Model for Immunomodulatory Drug-Associated Thrombosis Among Patients With Multiple Myeloma.

BACKGROUND: Although venous thromboembolism (VTE) is a significant complication for patients with multiple myeloma (MM) receiving immunomodulatory drugs (IMiDs), no validated clinical model predicts VTE in this population. This study aimed to derive and validate a new risk assessment model (RAM) for IMiD-associated VTE. METHODS: Patients with newly diagnosed MM receiving IMiDs were selected from the SEER-Medicare database (n=2,397) to derive a RAM and then data from the Veterans Health Administration database (n=1,251) were used to externally validate the model. A multivariable cause-specific Cox regression model was used for model development. RESULTS: The final RAM, named the "SAVED" score, included 5 clinical variables: prior surgery, Asian race, VTE history, age ≥80 years, and dexamethasone dose. The model stratified approximately 30% of patients in both the derivation and the validation cohorts as high-risk. Hazard ratios (HRs) were 1.85 (P<.01) and 1.98 (P<.01) for high- versus low-risk groups in the derivation and validation cohorts, respectively. In contrast, the method of stratification recommended in the current NCCN Guidelines for Cancer-Associated Venous Thromboembolic Disease had HRs of 1.21 (P=.17) and 1.41 (P=.07) for the corresponding risk groups in the 2 datasets. CONCLUSIONS: The SAVED score outperformed the current NCCN Guidelines in risk-stratification of patients with MM receiving IMiD therapy. This clinical model can help inform providers and patients of VTE risk before IMiD initiation and provides a simplified clinical backbone for further prognostic biomarker development in this population.

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3) and processed meat consumption (OR = 1.17; p = 8.7E-09), which was consistently observed across studies (p heterogeneity = 0.78). The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively) and null among those with the GG genotype (OR = 1.03). Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.

CYP24A1 variant modifies the association between use of oestrogen plus progestogen therapy and colorectal cancer risk.

BACKGROUND: Menopausal hormone therapy (MHT) use has been consistently associated with a decreased risk of colorectal cancer (CRC) in women. Our aim was to use a genome-wide gene-environment interaction analysis to identify genetic modifiers of CRC risk associated with use of MHT. METHODS: We included 10 835 postmenopausal women (5419 cases and 5416 controls) from 10 studies. We evaluated use of any MHT, oestrogen-only (E-only) and combined oestrogen-progestogen (E+P) hormone preparations. To test for multiplicative interactions, we applied the empirical Bayes (EB) test as well as the Wald test in conventional case-control logistic regression as primary tests. The Cocktail test was used as secondary test. RESULTS: The EB test identified a significant interaction between rs964293 at 20q13.2/CYP24A1 and E+P (interaction OR (95% CIs)=0.61 (0.52-0.72), P=4.8 × 10(-9)). The secondary analysis also identified this interaction (Cocktail test OR=0.64 (0.52-0.78), P=1.2 × 10(-5) (alpha threshold=3.1 × 10(-4)). The ORs for association between E+P and CRC risk by rs964293 genotype were as follows: C/C, 0.96 (0.61-1.50); A/C, 0.61 (0.39-0.95) and A/A, 0.40 (0.22-0.73), respectively. CONCLUSIONS: Our results indicate that rs964293 modifies the association between E+P and CRC risk. The variant is located near CYP24A1, which encodes an enzyme involved in vitamin D metabolism. This novel finding offers additional insight into downstream pathways of CRC etiopathogenesis.

Toward Rigorous Data Harmonization in Cancer Epidemiology Research: One Approach.

Cancer epidemiologists have a long history of combining data sets in pooled analyses, often harmonizing heterogeneous data from multiple studies into 1 large data set. Although there are useful websites on data harmonization with recommendations and support, there is little research on best practices in data harmonization; each project conducts harmonization according to its own internal standards. The field would be greatly served by charting the process of data harmonization to enhance the quality of the harmonized data. Here, we describe the data harmonization process utilized at the Fred Hutchinson Cancer Research Center (Seattle, Washington) by the coordinating centers of several research projects. We describe a 6-step harmonization process, including: 1) identification of questions the harmonized data set is required to answer; 2) identification of high-level data concepts to answer those questions; 3) assessment of data availability for data concepts; 4) development of common data elements for each data concept; 5) mapping and transformation of individual data points to common data elements; and 6) quality-control procedures. Our aim here is not to claim a "correct" way of doing data harmonization but to encourage others to describe their processes in order that we can begin to create rigorous approaches. We also propose a research agenda around this issue.

Association of aspirin and NSAID use with risk of colorectal cancer according to genetic variants.

IMPORTANCE: Use of aspirin and other nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with lower risk of colorectal cancer. OBJECTIVE: To identify common genetic markers that may confer differential benefit from aspirin or NSAID chemoprevention, we tested gene × environment interactions between regular use of aspirin and/or NSAIDs and single-nucleotide polymorphisms (SNPs) in relation to risk of colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS: Case-control study using data from 5 case-control and 5 cohort studies initiated between 1976 and 2003 across the United States, Canada, Australia, and Germany and including colorectal cancer cases (n=8634) and matched controls (n=8553) ascertained between 1976 and 2011. Participants were all of European descent. EXPOSURES: Genome-wide SNP data and information on regular use of aspirin and/or NSAIDs and other risk factors. MAIN OUTCOMES AND MEASURES: Colorectal cancer. RESULTS: Regular use of aspirin and/or NSAIDs was associated with lower risk of colorectal cancer (prevalence, 28% vs 38%; odds ratio [OR], 0.69 [95% CI, 0.64-0.74]; P = 6.2 × 10(-28)) compared with nonregular use. In the conventional logistic regression analysis, the SNP rs2965667 at chromosome 12p12.3 near the MGST1 gene showed a genome-wide significant interaction with aspirin and/or NSAID use (P = 4.6 × 10(-9) for interaction). Aspirin and/or NSAID use was associated with a lower risk of colorectal cancer among individuals with rs2965667-TT genotype (prevalence, 28% vs 38%; OR, 0.66 [95% CI, 0.61-0.70]; P = 7.7 × 10(-33)) but with a higher risk among those with rare (4%) TA or AA genotypes (prevalence, 35% vs 29%; OR, 1.89 [95% CI, 1.27-2.81]; P = .002). In case-only interaction analysis, the SNP rs16973225 at chromosome 15q25.2 near the IL16 gene showed a genome-wide significant interaction with use of aspirin and/or NSAIDs (P = 8.2 × 10(-9) for interaction). Regular use was associated with a lower risk of colorectal cancer among individuals with rs16973225-AA genotype (prevalence, 28% vs 38%; OR, 0.66 [95% CI, 0.62-0.71]; P = 1.9 × 10(-30)) but was not associated with risk of colorectal cancer among those with less common (9%) AC or CC genotypes (prevalence, 36% vs 39%; OR, 0.97 [95% CI, 0.78-1.20]; P = .76). CONCLUSIONS AND RELEVANCE: In this genome-wide investigation of gene × environment interactions, use of aspirin and/or NSAIDs was associated with lower risk of colorectal cancer, and this association differed according to genetic variation at 2 SNPs at chromosomes 12 and 15. Validation of these findings in additional populations may facilitate targeted colorectal cancer prevention strategies.

Gene-environment interaction involving recently identified colorectal cancer susceptibility Loci.

BACKGROUND: Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer. Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS: Data on 9,160 cases and 9,280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, postmenopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS: None of the permutation-adjusted P values reached statistical significance. CONCLUSIONS: The associations between recently identified genetic susceptibility loci and colorectal cancer are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT: Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for colorectal cancer taken one at a time.

A pooled analysis of smoking and colorectal cancer: timing of exposure and interactions with environmental factors.

BACKGROUND: Considerable evidence suggests that cigarette smoking is associated with a higher risk of colorectal cancer (CRC). What is unclear, however, is the impact of quitting smoking on risk attenuation and whether other risk factors for CRC modify this association. METHODS: We conducted a pooled analysis of eight studies, including 6,796 CRC cases and 7,770 controls, to evaluate the association between cigarette smoking history and CRC risk and to investigate potential effect modification by other risk factors. RESULTS: Current smokers [OR, 1.26; 95% confidence interval (CI), 1.11-1.43] and former smokers (OR, 1.18; 95% CI, 1.09-1.27), relative to never smokers, showed higher risks of CRC. Former smokers remained at higher CRC risk, relative to never smokers, for up to about 25 years after quitting. The impact of time since quitting varied by cancer subsite: The excess risk due to smoking decreased immediately after quitting for proximal colon and rectal cancer but not until about 20 years post-quitting for distal colon cancer. Furthermore, we observed borderline statistically significant additive interactions between smoking status and body mass index [BMI; relative excess risk due to interaction (RERI]), 0.15; 95% CI, -0.01 to 0.31; P = 0.06] and significant additive interaction between smoking status and fruit consumption (RERI, 0.16; 95% CI, 0.01-0.30; P = 0.04). CONCLUSION: CRC risk remained increased for about 25 years after quitting smoking, and the pattern of decline in risk varied by cancer subsite. BMI and fruit intake modified the risk associated with smoking. IMPACT: These results contribute to a better understanding of the mechanisms through which smoking impacts CRC etiology.

Characterization of gene-environment interactions for colorectal cancer susceptibility loci.

Genome-wide association studies (GWAS) have identified more than a dozen loci associated with colorectal cancer (CRC) risk. Here, we examined potential effect-modification between single-nucleotide polymorphisms (SNP) at 10 of these loci and probable or established environmental risk factors for CRC in 7,016 CRC cases and 9,723 controls from nine cohort and case-control studies. We used meta-analysis of an efficient empirical-Bayes estimator to detect potential multiplicative interactions between each of the SNPs [rs16892766 at 8q23.3 (EIF3H/UTP23), rs6983267 at 8q24 (MYC), rs10795668 at 10p14 (FLJ3802842), rs3802842 at 11q23 (LOC120376), rs4444235 at 14q22.2 (BMP4), rs4779584 at 15q13 (GREM1), rs9929218 at 16q22.1 (CDH1), rs4939827 at 18q21 (SMAD7), rs10411210 at 19q13.1 (RHPN2), and rs961253 at 20p12.3 (BMP2)] and select major CRC risk factors (sex, body mass index, height, smoking status, aspirin/nonsteroidal anti-inflammatory drug use, alcohol use, and dietary intake of calcium, folate, red meat, processed meat, vegetables, fruit, and fiber). The strongest statistical evidence for a gene-environment interaction across studies was for vegetable consumption and rs16892766, located on chromosome 8q23.3, near the EIF3H and UTP23 genes (nominal P(interaction) = 1.3 × 10(-4); adjusted P = 0.02). The magnitude of the main effect of the SNP increased with increasing levels of vegetable consumption. No other interactions were statistically significant after adjusting for multiple comparisons. Overall, the association of most CRC susceptibility loci identified in initial GWAS seems to be invariant to the other risk factors considered; however, our results suggest potential modification of the rs16892766 effect by vegetable consumption.