Adherence to adjuvant endocrine therapy among breast cancer survivors: a systematic review and meta-synthesis of the qualitative literature using grounded theory

Purpose: Numerous studies have examined non-adherence to adjuvant endocrine therapy in women recovering from breast cancer, but none provide a comprehensive theory to explain the challenges of long-term medication-taking and resilience needed to continue. The aim of this study was to source, appraise, and synthesise data from existing qualitative studies to develop an in-depth explanatory model of non-adherence and discontinuation of hormonal medication among breast cancer survivors. Methods: A comprehensive search of databases and the literature identified 24 eligible qualitative studies published 2010-2019. Quotations (n= 801) listed within these papers and the original author interpretations were synthesised using NVivo, and grounded theory methodology. Results: At the beginning, knowledge about adjuvant endocrine therapy, trust in doctors, and worries and expectations, mean agreeing to medication is the only viable option, akin to a Hobson’s choice. Thereafter, women’s ability to deal with medication side-effects, knowledge, and support received affect their decision to continue, akin to a horned dilemma where giving up the medication risks cancer recurrence, and continuing means reduced contentment. Women stopping medication altogether question treatment necessity, search for normalcy, and prioritise quality of life. Conclusion: Shared experiences and understandings were uncovered by examining commonalities in existing publications. The core category explained the difficulties women face with the initial decision to accept long-term endocrine therapy and then the everyday challenges of continuing or deciding to stop treatment early. An educational tool to inform survivors and health professionals about these challenges could potentially improve women’s experience on treatment and in turn their adherence

Aspirin use and survival after the diagnosis of breast cancer:a population-based cohort study

Background: Aspirin use has been associated with a reduced cancer incidence and fewer deaths from cancer. This study examined whether women with breast cancer prescribed aspirin postdiagnosis had improved survival.Methods:An observational, population cohort study was undertaken using data linkage of cancer registry, dispensed prescriptions and death records in Tayside, Scotland. All community prescriptions for aspirin in women with breast cancer were extracted and use postdiagnosis for each individual examined using Cox's proportional hazard models. The main outcome measures were all-cause mortality and breast cancer-specific mortality.Results:Four thousand six hundred and twenty-seven patients diagnosed with breast cancer between 1 January 1998 and 31 December 2008 were followed up until 28 February 2010. Median age at diagnosis was 62 (IQR 52-74). One thousand eight hundred and two (39%) deaths were recorded, with 815 (18%) attributed to breast cancer. One thousand and thirty-five (22%) patients were prescribed aspirin postdiagnosis. Such aspirin use was associated with lower risk of all-cause mortality (HR=0.53, 95% CI=0.45-0.63, P<0.001) and breast cancer-specific mortality (HR=0.42, 95% CI=0.31-0.55, P<0.001) after adjusting for age, socioeconomic status, TNM stage, tumour grade, oestrogen receptor status, surgery, radiotherapy, chemotherapy, adjuvant endocrine therapy and aspirin use prediagnosis. Conclusions:Aspirin use postdiagnosis of breast cancer may reduce both all-cause and breast cancer-specific mortality. Further investigation seeking a causal relationship and which subgroups of patients benefit most await ongoing randomised controlled trials.Publisher PDFPeer reviewe

The rising tide of polypharmacy and drug-drug interactions:population database analysis 1995-2010

Background: The escalating use of prescribed drugs has increasingly raised concerns about polypharmacy. This study aims to examine changes in rates of polypharmacy and potentially serious drug-drug interactions in a stable geographical population between 1995 and 2010. Methods: This is a repeated cross-sectional analysis of community-dispensed prescribing data for all 310,000 adults resident in the Tayside region of Scotland in 1995 and 2010. The number of drug classes dispensed and the number of potentially serious drug-drug interactions (DDIs) in the previous 84 days were calculated, and age-sex standardised rates in 1995 and 2010 compared. Patient characteristics associated with receipt of ≥10 drugs and with the presence of one or more DDIs were examined using multilevel logistic regression to account for clustering of patients within primary care practices. Results: Between 1995 and 2010, the proportion of adults dispensed ≥5 drugs doubled to 20.8%, and the proportion dispensed ≥10 tripled to 5.8%. Receipt of ≥10 drugs was strongly associated with increasing age (20-29 years, 0.3%; ≥80 years, 24.0%; adjusted OR, 118.3; 95% CI, 99.5-140.7) but was also independently more common in people living in more deprived areas (adjusted OR most vs. least deprived quintile, 2.36; 95% CI, 2.22-2.51), and in people resident in a care home (adjusted OR, 2.88; 95% CI, 2.65-3.13). The proportion with potentially serious drug-drug interactions more than doubled to 13% of adults in 2010, and the number of drugs dispensed was the characteristic most strongly associated with this (10.9% if dispensed 2-4 drugs vs. 80.8% if dispensed ≥15 drugs; adjusted OR, 26.8; 95% CI 24.5-29.3). Conclusions: Drug regimens are increasingly complex and potentially harmful, and people with polypharmacy need regular review and prescribing optimisation. Research is needed to better understand the impact of multiple interacting drugs as used in real-world practice and to evaluate the effect of medicine optimisation interventions on quality of life and mortality.Publisher PDFPeer reviewe

Understanding Variation in Sets of N-of-1 Trials.

A recent paper in this journal by Chen and Chen has used computer simulations to examine a number of approaches to analysing sets of n-of-1 trials. We have examined such designs using a more theoretical approach based on considering the purpose of analysis and the structure as regards randomisation that the design uses. We show that different purposes require different analyses and that these in turn may produce quite different results. Our approach to incorporating the randomisation employed when the purpose is to test a null hypothesis of strict equality of the treatment makes use of Nelder's theory of general balance. However, where the purpose is to make inferences about the effects for individual patients, we show that a mixed model is needed. There are strong parallels to the difference between fixed and random effects meta-analyses and these are discussed

Tamoxifen metabolism predicts drug concentrations and outcome in premenopausal patients with early breast cancer

Tamoxifen is the standard-of-care treatment for estrogen receptor-positive premenopausal breast cancer. We examined tamoxifen metabolism via blood metabolite concentrations and germline variations of CYP3A5, CYP2C9, CYP2C19 and CYP2D6 in 587 premenopausal patients (Asians, Middle Eastern Arabs, Caucasian-UK; median age 39 years) and clinical outcome in 306 patients. N-desmethyltamoxifen (DM-Tam)/(Z)-endoxifen and CYP2D6 phenotype significantly correlated across ethnicities (R2: 53%, P&lt;10?77). CYP2C19 and CYP2C9 correlated with norendoxifen and (Z)-4-hydroxytamoxifen concentrations, respectively (P&lt;0.001). DM-Tam was influenced by body mass index (P&lt;0.001). Improved distant relapse-free survival (DRFS) was associated with decreasing DM-Tam/(Z)-endoxifen (P=0.036) and increasing CYP2D6 activity score (hazard ratio (HR)=0.62; 95% confidence interval (CI), 0.43–0.91; P=0.013). Low (&lt;14?nM) compared with high (&gt;35?nM) endoxifen concentrations were associated with shorter DRFS (univariate P=0.03; multivariate HR=1.94; 95% CI, 1.04–4.14; P=0.064). Our data indicate that endoxifen formation in premenopausal women depends on CYP2D6 irrespective of ethnicity. Low endoxifen concentration/formation and decreased CYP2D6 activity predict shorter DRFS

Planning and analysis of cross-over trials in infertility

The use of cross-over trials in investigating treatments for infertility is discussed. A simple possible approach to analyzing such trials using the Mantel–Haenszel procedure is explained. A more flexible approach based on the normal–binomial mixture model of Ezzet and Whitehead is examined. It is shown how this may be implemented in various statistical packages by applying it to two real examples of trials in infertility. An approach that may be used to compare designs via simulation is explained briefly. It is concluded that provided that cross-over trials in infertility are regarded as parallel group trials with extra information rather than as cross-over trials with missing information, their use may be more promising than that has previously been concluded