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Much preclinical and epidemiological evidence supports the anticancer effects of statins. Epidemiological evidence does not suggest an association between statin use and reduced incidence of breast cancer, but does support a protective effect of statins—especially simvastatin—on breast cancer recurrence. Here, we argue that the existing evidence base is sufficient to justify a clinical trial of breast cancer adjuvant therapy with statins and we advocate for such a trial to be initiated without delay. If a protective effect of statins on breast cancer recurrence is supported by trial evidence, then the indications for a safe, well tolerated, and inexpensive treatment can be expanded to improve outcomes for breast cancer survivors. We discuss several trial design opportunities—including candidate predictive biomarkers of statin safety and efficacy—and offer solutions to the key challenges involved in the enrolment, follow-up, and analysis of such a trial.

Introduction Patients with hormone receptor positive breast cancer are recommended at least five years of adjuvant endocrine therapy, but adherence to this treatment is often suboptimal. We investigated longitudinal trends in adjuvant endocrine therapy (AET) adherence among premenopausal breast cancer patients and identified clinical characteristics, including baseline comorbidities and non-cancer chronic medication use, associated with AET adherence. Methods We included stage I–III premenopausal breast cancer patients diagnosed during 2002–2011 and registered in the Danish Breast Cancer Group clinical database who initiated AET. We used group-based trajectory modeling to describe AET adherence patterns. We also linked patients to Danish population-based registries and fit multinomial logistic models to compute odds ratios (ORs) and 95% confidence intervals (95% CIs) associating clinical characteristics with AET adherence patterns. Results We identified three adherence patterns among 4,353 women—high adherers (57%), slow decliners (36%), and rapid decliners (6.9%). Women with stage I disease (vs. stage II; OR: 1.9, 95% CI 1.5, 2.5), without chemotherapy (vs. chemotherapy; OR: 4.3, 95% CI 3.0, 6.1), with prevalent comorbid disease (Charlson Comorbidity Index score ≥ 1 vs. 0; OR: 1.6, 95% CI 1.1, 2.3), and with a history of chronic non-cancer medication use (vs. none; OR: 1.3, 95% CI 1.0, 1.8) were more likely to be rapid decliners compared with high adherers. Conclusions Women with stage I cancer, no chemotherapy, higher comorbidity burden, and history of chronic non-cancer medication use were less likely to adhere to AET. Taking steps to promote adherence in these groups of women may reduce their risk of recurrence.

Background Premenopausal women diagnosed with estrogen receptor (ER)-positive breast cancer are prescribed 5–10 years of tamoxifen therapy to prevent or delay a recurrence. The enzymes 17β-hydroxysteroid dehydrogenase 1 and 2 (HSD17B1 and HSD17B2, respectively) regulate the relative concentrations of estrogen metabolites and may modify tamoxifen effectiveness. We evaluated the prognostic and predictive value of HSD17B1 and HSD17B2 expression in breast tumors. Methods We identified a cohort of premenopausal breast cancer patients from the Danish Breast Cancer Group database (2002–2011) and stratified on ER status and receipt of tamoxifen (4600 ER+/TAM + and 1359 ER−/TAM−). Biomarkers HSD17B1 and HSD17B2 were assayed by immunohistochemistry. We used Cox proportional hazards regression to compute the hazard ratios (HRs) and 95% simulation intervals (SIs) associating each biomarker with recurrence, with bias adjustment to account for mismeasurement of biomarker expression and baseline selection bias from tumor sample availability. Results Among ER+/TAM + breast cancers, 24% had any HSD17B1 expression compared with 13% of ER−/TAM − breast cancers. In the bias-adjusted analyses, women diagnosed with tumors positive for HSD17B1 expression had a slight increased rate of recurrence: HR = 1.13 (95% SI 0.90, 1.43) in the ER+/TAM + stratum and HR = 1.15 (95% SI 0.77, 1.79) in the ER−/TAM − stratum. A 10-unit increase in HSD17B2 expression corresponded with a decrease in the estimated rate of recurrence among ER+/TAM + patients (HR = 0.85, 95% SI 0.69, 1.05), but not among ER−/TAM − patients (HR = 1.07, 95% SI 0.82, 1.42). Conclusions HSD17B1 may be a prognostic marker for recurrence and HSD17B2 may be predictive of response to tamoxifen therapy in breast cancer.

Background Hypoxia-inducible factor-1α (HIF-1α) is a transcription factor that facilitates the adaptation of cancer cells to hypoxic conditions and may be prognostic of breast cancer recurrence. We evaluated the association of HIF-1α expression with breast cancer recurrence, and its association with timing of breast cancer recurrence. Methods In this population-based case-control study, we included women diagnosed with stage I–III breast cancer between 1985 and 2001, aged 35–69 years, registered in the Danish Breast Cancer Group. We identified 541 cases of breast cancer recurrence among women with estrogen receptor (ER)-positive disease who were treated with tamoxifen for at least 1 year (ER+ TAM+). We also enrolled 300 breast cancer recurrence cases among women with ER-negative disease, not treated with tamoxifen, who survived at least 1 year (ER−/TAM−). Controls were recurrence-free breast cancer patients at the time of case diagnosis, matched to recurrence cases on ER/TAM status, date of surgery, menopausal status, cancer stage, and county of residence. Expression of HIF-1α was measured by immunohistochemistry on tissue microarrays. We fitted logistic regression models to compute odds ratios (ORs) and 95% confidence intervals (CIs) associating HIF-1α expression with recurrence, and with timing of recurrence. Results HIF-1α expression was observed in 23% of cases and 20% of controls in the ER+/TAM+ stratum, and in 47% of cases and 48% of controls in the ER−/TAM− stratum. We observed a near-null association between HIF-1α expression in both ER/TAM groups (ER+/TAM+ OR = 1.21, 95%CI 0.88, 1.67 and ER−/TAM− OR = 0.97, 95%CI 0.68, 1.39). HIF-1α expression was not associated with time to recurrence among women in the ER+/TAM+ stratum, but was associated with early recurrence among women in the ER−/TAM− stratum. Conclusion In this study, HIF-1α expression was not associated with breast cancer recurrence overall but may be associated with early recurrence among women diagnosed with ER− breast cancer.

The role of cytochrome P450 drug metabolizing enzymes in the efficacy of tamoxifen treatment of breast cancer is subject to substantial interest and controversy. CYP2D6 have been intensively studied, but the role of CYP2C19 is less elucidated, and we studied the association of CYPC19 genotype and recurrence of breast cancer. We used outcome and genotyping data from the large publicly available International Tamoxifen Pharmacogenomics Consortium (ITPC) dataset. Cox regression was used to compute the hazard ratios (HRs) for recurrence. CYP2C19 genotype data was available for 2 423 patients and the final sample cohort comprised 2 102 patients. CYP2C19*2 or *19 alleles did not influence DFS. For the CYP2C19*2 allele, the HR was 1.05 (CI 0.78–1.42) and 0.79 (CI 0.32–1.94) for hetero- and homozygote carriers, respectively. The corresponding HR for hetero- and homozygote carriers of the CYP2C19*17 allele were 1.02 (CI 0.71–1.46) and 0.57 (CI 0.26–1.24), respectively. Accounting for CYP2D6 genotype status did not change these estimates. We found no evidence to support a clinically meaningful role of CYP2C19 polymorphisms and response to tamoxifen in breast cancer patients and, consequently, CYP2C19 genotype status should not be included in clinical decisions on tamoxifen treatment.

Purpose: To compare the magnitude of bias due to unmeasured confounding estimated from various techniques in an applied example. Patients and Methods: We examined the association between dibutyl phthalate (DBP) and incident estrogen receptor (ER)-positive breast cancer in a Danish nationwide cohort (N=1,122,042). Cox regression analyses were adjusted for age and active drug compounds contributing to DBP exposure. We estimated the hazard ratios (HRs) that would have been observed had one of the DBP sources been unmeasured and calculated the strength of confounding by comparing to the fully adjusted HR. We performed a quantitative bias analysis (QBA) of the \"unmeasured\" confounder, using external information to specify the bias parameters. Upper bounds on the bias were estimated and E-values were calculated. Results: The adjusted HR for incident ER-positive breast cancer among women with high-level ([greater than or equal to]10,000 cumulative milligrams) versus no DBP exposure was 2.12 (95% confidence interval 1.12 to 4.05). Removing each DBP source in isolation resulted in negligible change in the HR. The bias estimates from the QBA ranged from 1.00 to 1.01. The estimated maximum impact of unmeasured confounding ranged from 1.01 to 1.51. E-values ranged from 3.46 to 3.68. Conclusion: The impact of bias due to simulated unmeasured confounding was negligible, in part, because the unmeasured variable was not independent of controlled variables. When a suspected confounder cannot be measured in the study data, our exercise suggests that QBA is the most informative method for assessing the impact. E-values may best be reserved for situations where uncontrolled confounding emanates from an unknown confounder. Keywords: bias analysis, unmeasured confounding, the E-value

Manganese superoxide dismutase (MnSOD) inhibits oxidative damage and cancer therapy effectiveness. A polymorphism in its encoding gene (SOD2: Val16Ala rs4880) may confer poorer breast cancer survival, but data are inconsistent. We examined the association of SOD2 genotype and breast cancer recurrence (BCR) among patients treated with cyclophosphamide-based chemotherapy (Cyclo). We compared our findings with published studies using meta-analyses. We conducted a population-based case-control study of BCR among women in Jutland, Denmark. Subjects were diagnosed with non-metastatic breast cancer from 1990-2001, received adjuvant Cyclo, and were registered in the Danish Breast Cancer Cooperative Group. We identified 118 patients with BCR and 213 matched breast cancer controls. We genotyped SOD2 and used conditional logistic regression to compute the odds ratio (OR) and associated 95% confidence intervals (95% CI) of BCR. We used random-effects meta-analytic models to evaluate the association of SOD2 polymorphisms and BCR. The frequency of the SOD2-Ala allele was 70% in cases versus 71% in controls; 40% versus 44% were heterozygotes, and 30% versus 25% were homozygotes, respectively. Heterozygote and homozygote carriers of the Ala allele had no increased rate of BCR (OR = 1.1, 95%CI = 0.65, 2.0, and OR = 0.87, 95%CI = 0.47, 1.6, respectively). Five studies informed the meta-analytic models; summary estimates associating BCR for homozygote, or any inheritance of the variant Ala allele were 1.18 (95%CI = 0.74, 1.88), and 1.18, (95%CI = 0.91, 1.54), respectively. Our findings do not suggest that MnSOD enzymatic activity, as measured by SOD2 genotype, affects rates of BCR among patients treated with Cyclo.

PurposeThe bovine leukemia virus (BLV) is a deltaretrovirus that causes malignant lymphoma and lymphosarcomas in cattle globally and has high prevalence among large scale U.S. dairy herds. Associations between presence of BLV DNA in human mammary tissue and human breast cancer incidence have been reported. We sought to estimate the prevalence of BLV DNA in breast cancer tissue samples in a rural state with an active dairy industry.MethodsWe purified genomic DNA from 56 fresh-frozen breast cancer tissue samples (51 tumor samples, 5 samples representing adjacent normal breast tissue) banked between 2016 and 2019. Using nested PCR assays, multiple BLV tax sequence primers and primers for the long terminal repeat (LTR) were used to detect BLV DNA in tissue samples and known positive control samples, including the permanently infected fetal lamb kidney cell line (FLK-BLV) and blood from BLV positive cattle.ResultsThe median age of patients from which samples were obtained at the time of treatment was 60 (40–93) and all were female. Ninety percent of patients had invasive ductal carcinoma. The majority were poorly differentiated (60%). On PCR assay, none of the tumor samples tested positive for BLV DNA, despite having consistent signals in positive controls.ConclusionWe did not find BLV DNA in fresh-frozen breast cancer tumors from patients presenting to a hospital in Vermont. Our findings suggest a low prevalence of BLV in our patient population and a need to reevaluate the association between BLV and human breast cancer.

Among men and women diagnosed with colorectal cancer (CRC), 20-50% will develop a cancer recurrence. Cancer recurrences are not routinely captured by most population-based registries; however, linkage across Danish registries allows for the development of predictive models to detect recurrence. Successful application of such models in population-based settings requires validation against a gold standard to ensure the accuracy of recurrence identification. We apply a recently developed validation study design for prospectively collected validation data to validate predicted CRC recurrences against gold standard diagnoses from medical records in an actively followed cohort of CRC patients in Denmark. We use a Bayesian monitoring framework, traditionally used in clinical trials, to iteratively update classification parameters (positive and negative predictive values, and sensitivity and specificity) in an adaptive validation substudy design. This design allows determination of the sample size necessary to estimate the corresponding parameters and to identify when validation efforts can cease based on predefined criteria for parameter values and levels of precision. Among 355 men and women diagnosed with CRC in Denmark and actively followed semi-annually, there were 63 recurrences diagnosed by active follow-up and 70 recurrences identified by a predictive algorithm. The adaptive validation design met stopping criteria for the classification parameters after 120 patients had their recurrence information validated. This stopping point yielded parameter estimates for the classification parameters similar to those obtained when the entire cohort was validated, with 66% less patients needed for the validation study. In this proof of concept application of the adaptive validation study design for outcome misclassification, we demonstrated the ability of the method to accurately determine when sufficient validation data have been collected. This method serves as a novel validation substudy design for prospectively collected data with simultaneous implementation of a validation study.