Predicting difference in mean survival time from cause-specific hazard ratios for women diagnosed with breast cancer.

BACKGROUND: Relative reduction in breast cancer mortality is the preferred outcome measure for evaluation of mammography screening. However, mean survival time has been advocated as a better and more intuitive outcome for risk communication. We have previously introduced a method to predict difference in mean survival time from empirical hazard ratios for all-cause mortality. In this article, we aim to investigate the association between hazard ratios for breast cancer mortality and the difference in mean survival time for women diagnosed with breast cancer. METHODS: We retrieved data on all women diagnosed with first-time invasive breast cancer in Norway from 1960 through 2004. Women were followed until emigration or end of follow-up on 31 December 2015, whichever came first. Observed differences in mean survival times and hazard ratios for both breast cancer death and death from causes other than breast cancer were obtained for neighbouring time periods defined by women's age and year of diagnosis. Based on previously developed methods, we fitted a linear relationship between observed differences in mean survival and logarithmic hazard ratios. RESULTS: A linear association was found between breast cancer-specific hazard ratios and difference in mean survival time for women diagnosed with breast cancer. This association was also estimated with adjustment for other causes of death than breast cancer. CONCLUSIONS: The change in mean survival time could be predicted from an estimated reduction in breast cancer mortality. This outcome measure can contribute to better and more understandable risk information about the effect of mammography screening programmes.

Negative controls to detect uncontrolled confounding in observational studies of mammographic screening comparing participants and non-participants.

BACKGROUND: When comparing mammography-screening participants and non-participants, estimates of reduction in breast-cancer mortality may be biased by poor baseline comparability. We used negative controls to detect uncontrolled confounding. METHODS: We designed a closed cohort of Danish women invited to a mammography-screening programme at age 50-52 years in Copenhagen or Funen from 1991 through 2001. We included women with a normal screening result in their first-invitation round. Based on their second-invitation round, women were divided into participants and non-participants and followed until death, emigration or 31 December 2014, whichever came first. We estimated hazard ratios (HRs) of death from breast cancer, causes other than breast cancer and external causes. We added dental-care participation as an exposure to test for an independent association with breast-cancer mortality. We adjusted for civil status, parity, age at first birth, educational attainment, income and hormone use. RESULTS: Screening participants had a lower hazard of breast-cancer death [HR 0.47, 95% confidence interval (CI) 0.32, 0.69] compared with non-participants. Participants also had a lower hazard of death from other causes (HR 0.43, 95% CI 0.39, 0.46) and external causes (HR 0.35, 95% CI 0.23, 0.54). Reductions persisted after covariate adjustment. Dental-care participants had a lower hazard of breast-cancer death (HR 0.75, 95% CI 0.56, 1.01), irrespective of screening participation. CONCLUSIONS: Negative-control associations indicated residual uncontrolled confounding when comparing breast-cancer mortality among screening participants and non-participants.

Predicting Difference in Mean Survival Time from Reported Hazard Ratios for Cancer Patients.

BACKGROUND: Gain in mean survival time from new cancer treatments is a core component of cost-effectiveness analyses frequently used by payers for reimbursement decisions. Due to limited follow-up time, clinical trials rarely report this measure, whereas they often report hazard ratios comparing treatment groups. AIM: We aimed to explore the empirical relationship between gain in mean survival time and the hazard ratio for cancer patients. METHODS: We included all patients in Norway diagnosed from 1965 through 2004 with late-stage cancer at the point of diagnosis and with one of the following cancers: stomach, colon, rectal, pancreas, lung and trachea, kidney excluding renal pelvis, and metastasized breast and prostate. Patients were followed until emigration, death, or June 30, 2016, whichever came first. Observed mean survival times and hazard ratios were obtained in subcohorts defined by patients' sex, age, cancer type, and time period of diagnosis, which had nearly complete follow-up. Based on theoretical considerations, we fitted a linear relationship between observed differences in mean survival and logarithmic hazard ratios. For validation, we estimated differences in mean survival from hazard ratios of bootstrap samples with artificially induced censoring and compared with fitting a Weibull distribution. RESULTS: The relationship between differences in mean survival time and corresponding logarithmic hazard ratios was linear for each of the included cancers. The predicted differences in mean survival of the empirical approach generally had smaller bias than the Weibull approach. CONCLUSION: For cancer diagnoses with poor prognosis, differences in mean survival times could be predicted from corresponding hazard ratios. This hazard ratio-based approach outperforms or is similar to fitting Weibull models to data with incomplete follow-up, while making fewer assumptions.

Effect of organized mammography screening on breast cancer mortality: A population-based cohort study in Norway.

We aimed to estimate the effect of organized mammography screening on incidence-based breast cancer mortality by comparing changes in mortality among women eligible for screening to concurrent changes in younger and older ineligible women. In a county-wise balanced, open-cohort study, we used birth cohorts (1896-1982) to construct three age groups in both the historical and screening period: women eligible for screening, and younger or older women ineligible for screening. We included women diagnosed with breast cancer who died within the same age-period group during 1987-2010 (n = 4,903). We estimated relative incidence-based mortality rate ratios (relative MRR) comparing temporal changes in eligible women to concurrent changes in ineligible women. Additionally, we conducted analyses comparing the change in eligible women to younger, ineligible women with either continued accrual and follow-up period (eligible women only) or continued follow-up period. All three age groups experienced a reduction in mortality, but the decrease among eligible women was about the same among ineligible women (relative MRR = 1.05, 95% CI: (0.94-1.18)). Varying the definition of follow-up yielded similar results. Mammography screening was not associated with a larger breast cancer mortality reduction in women eligible relative to ineligible women.

An introduction to instrumental variable assumptions, validation and estimation.

The instrumental variable method has been employed within economics to infer causality in the presence of unmeasured confounding. Emphasising the parallels to randomisation may increase understanding of the underlying assumptions within epidemiology. An instrument is a variable that predicts exposure, but conditional on exposure shows no independent association with the outcome. The random assignment in trials is an example of what would be expected to be an ideal instrument, but instruments can also be found in observational settings with a naturally varying phenomenon e.g. geographical variation, physical distance to facility or physician's preference. The fourth identifying assumption has received less attention, but is essential for the generalisability of estimated effects. The instrument identifies the group of compliers in which exposure is pseudo-randomly assigned leading to exchangeability with regard to unmeasured confounders. Underlying assumptions can only partially be tested empirically and require subject-matter knowledge. Future studies employing instruments should carefully seek to validate all four assumptions, possibly drawing on parallels to randomisation.

Benefits and harms of mammography screening.

Mammography screening for breast cancer is widely available in many countries. Initially praised as a universal achievement to improve women's health and to reduce the burden of breast cancer, the benefits and harms of mammography screening have been debated heatedly in the past years. This review discusses the benefits and harms of mammography screening in light of findings from randomized trials and from more recent observational studies performed in the era of modern diagnostics and treatment. The main benefit of mammography screening is reduction of breast-cancer related death. Relative reductions vary from about 15 to 25% in randomized trials to more recent estimates of 13 to 17% in meta-analyses of observational studies. Using UK population data of 2007, for 1,000 women invited to biennial mammography screening for 20 years from age 50, 2 to 3 women are prevented from dying of breast cancer. All-cause mortality is unchanged. Overdiagnosis of breast cancer is the main harm of mammography screening. Based on recent estimates from the United States, the relative amount of overdiagnosis (including ductal carcinoma in situ and invasive cancer) is 31%. This results in 15 women overdiagnosed for every 1,000 women invited to biennial mammography screening for 20 years from age 50. Women should be unpassionately informed about the benefits and harms of mammography screening using absolute effect sizes in a comprehensible fashion. In an era of limited health care resources, screening services need to be scrutinized and compared with each other with regard to effectiveness, cost-effectiveness and harms.