Breast cancer incidence and survival trends by molecular subtypes in Scotland

Background: Breast cancer (BC) is the most common cancer among women and leading contributor to cancer mortality, hence constitutes a major public health issue worldwide. In Scotland, over 4,000 women are diagnosed with BC every year and around a 1,000 die from this disease. Monitoring incidence, mortality and survival trends is key for surveillance of disease progression. BC is heterogeneous, with multiple subtypes defined by molecular markers, such as the oestrogen receptor (ER), that have different aetiology, targeted treatments and prognosis, yet standard reporting of incidence and mortality rates is not usually done using tumour marker data. The Scottish Cancer Registry was the first registry in the UK to collect molecular marker data and therefore, constitutes an excellent opportunity to explore incidence and survival trends over time by molecular subtypes. This PhD aims to describe temporal trends in BC incidence and survival by molecular subtypes in Scotland to inform public health prevention programmes, diagnostic and therapeutic services. Methods: A systematic review was conducted to determine the extent of available data on BC incidence trends by ER in population-based studies of women of European ancestry. In addition, the Scottish Cancer registry data on over 72,000 women diagnosed with incident primary BC from 1997 to 2016 (the focus of most analyses for this dissertation) was used to describe trends in incidence and survival in Scotland. Age-standardised incidence rates (ASiR) and age-specific incidence were estimated by BC subtype after imputation of molecular marker data. Joinpoint regression and age-period-cohort (APC) models were used to assess whether significant differences were observed in incidence trends by ER, the human epidermal growth factor receptor 2 (HER2) and the immunohistochemistry (IHC) defined molecular subtypes. Kaplan-Meier (KM) estimates and traditional and extended Cox proportional hazards models were computed to assess breast cancer specific survival (BCSS) by BC subtypes. Sensitivity analysis was carried out to compare results for the Cox models from complete case analysis (CCA) and multiple imputation analysis (MIA). The effect of individual, tumour characteristics and treatments on BCSS for each subtype was also investigated. Trends in 5-year survival by age, grade and stage characteristics for the different subtypes (ER+ and ER-) were investigated to identify the characteristics of women showing greatest and lowest improvements over time. Other causes of death were also explored and cumulative incidence functions (CIF) were investigated. Results: The systematic review showed that ER+ BC incidence increased and ER- BC incidence decreased in the last four decades (EAPCs ranging from 0.8% to 3% for ER+ tumours and -2.1% to -3.4% for ER- tumours) and that the rise in overall incidence trends is mainly driven by increases of ER+ tumours in women of screening age. In Scotland, BC incidence rates showed the same divergent pattern between ER+ and ER- tumours observed in other countries. ER+ tumour incidence increased by 0.4% per year from 1997 to 2011 and increases were mainly among routinely screened women aged 50 to 69 years. In contrast, ER- tumour incidence decreased among all ages by -2.5% per year over the study period. Apart from the period effects observed, APC models showed that older cohorts of women born in 1912-1940 had lower incidence rate ratios (IRR) for ER+ tumours, and younger cohort of women born in 1960-1986 had lower IRR for ER- tumours, compared to women from the 1941-1959 birth cohorts. Results for the IHC defined subtypes showed that luminal A tumours, that account for more than half of all tumours, had similar patterns to those observed for ER+ tumours, with increases until 2011. In contrast, luminal B tumours declined over time, particularly in women over 50 years of age. There was no clear trend for HER2-enriched or triple negative breast cancers (TNBC) overall but TNBC tumours seemed to increase in younger women aged 20 to 49 years. BCSS also differed between subtypes with ER+ tumours having better survival than ER- tumours, luminal A tumours having the best survival of all IHC defined subtypes and TNBC having the worst survival. Age, grade, stage, screening and surgery were the most important prognostic factors irrespective of tumour subtype, with women who had older age, higher grade, stages III-IV, tumours not screen detected and who did not have surgery having worse survival. Deprivation was also associated with lower BCSS, with women living in the most deprived areas of Scotland having increased BC-specific mortality when compared to women in the least deprived areas and this relationship was observed for all subtypes with slightly higher HR for HER2-enriched subtypes (but wider CI). Five-year BCSS trends showed improvements in the last two decades, especially for women aged 50 to 69 years. The greatest gains in survival were seeing in women with advanced tumours (high grade or stage III-IV tumours) and ER-tumours seemed to have greatest improvements than ER+ tumours, although their survival remained lower than for ER+ tumours. The improvements observed for women with high grade and stage III-IV tumours were observed in both screen and not screen detected tumours but the rise was sharper amongst women with screen detected tumours. Women younger than 50 years showed similar improvements than those observed in women aged 50 to 69 years. Older women aged 70 years or more showed no consistent survival improvements over time and over 50% of women in that age had a primary cause of death other than BC with cardiovascular diseases (CVD) being a major contributor (22% of all deaths). Conclusions: This project is the first in the UK to describe incidence and survival trends by molecular subtypes of BC using population-based data. Divergent incidence trends found in Scotland are similar to those observed in other countries and confirm different aetiology of BC molecular subtypes. Increases in the incidence of hormone sensitive tumours are likely to be driven by the implementation of mammographic screening programmes, population aging and changes in risk factors (RFs) that have differential effects on the subtypes, such as, reproductive factors and obesity. Survival improvements in Scotland are likely due to multiple contributors with two major factors such as screening and the improvement and development of new treatments likely playing a role. This PhD has allowed us to further understand disease progression of the different subtypes in Scotland and has identified groups of women (those with advanced tumour characteristics, living in the most deprived regions of Scotland or women aged 70 years or older) with lower survival and/or lower improvements in survival trends that could benefit from further prevention and treatment programmes. This PhD also highlights the importance of monitoring future incidence and survival by molecular subtypes to inform clinical planning and cancer control programmes

Quantity and quality of interaction between staff and older patients in UK hospital wards: A descriptive study

AbstractBackgroundThe quality of staff-patient interactions underpins the overall quality of patient experience and can affect other important outcomes. However no studies have been identified that comprehensively explore both the quality and quantity of interactions in general hospital settings.Aims & objectivesTo quantify and characterise the quality of staff-patient interactions and to identify factors associated with negative interaction ratings.SettingData were gathered at two acute English NHS hospitals between March and April 2015. Six wards for adult patients participated including medicine for older people (n=4), urology (n=1) and orthopaedics (n=1).MethodsEligible patients on participating wards were randomly selected for observation. Staff-patient interactions were observed using the Quality of Interactions Schedule. 120h of care were observed with each 2h observation session determined from a balanced random schedule (Monday-Friday, 08:00-22:00h). Multilevel logistic regression models were used to determine factors associated with negative interactions.Results1554 interactions involving 133 patients were observed. The median length of interaction was 36s with a mean of 6 interactions per patient per hour. Seventy three percent of interactions were categorized as positive, 17% neutral and 10% negative. Forty percent of patients had at least one negative interaction (95% confidence interval 32% to 49%). Interactions initiated by the patient (adjusted Odds Ratio [OR] 5.30), one way communication (adjusted OR 10.70), involving two or more staff (adjusted OR 5.86 for 2 staff, 6.46 for 3+ staff), having a higher total number of interactions (adjusted OR 1.09 per unit increase), and specific types of interaction content were associated with increased odds of negative interaction (p<0.05). In the full multivariable model there was no significant association with staff characteristics, skill mix or staffing levels. Patient agitation at the outset of interaction was associated with increased odds of negative interaction in a reduced model. There was no significant association with gender, age or cognitive impairment. There was substantially more variation at ward level (variance component 1.76) and observation session level (3.49) than at patient level (0.09).ConclusionThese findings present a unique insight into the quality and quantity of staff-patient interactions in acute care. While a high proportion of interactions were positive, findings indicate that there is scope for improvement. Future research should focus on further exploring factors associated with negative interactions, such as workload and ward culture

The landscape of the methodology in drug repurposing using human genomic data:a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record (EHR) data, public availability of various databases containing biological and clinical information, and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1st May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies, and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies

Reproductive history differs by molecular subtypes of breast cancer among women aged ≤50 years in Scotland in 2009-16:A cross-sectional study

BACKGROUND: The aetiology of breast cancers diagnosed ≤ 50 years of age remains unclear. We aimed to compare reproductive risk factors between molecular subtypes of breast cancer, thereby suggesting possible aetiologic clues, using routinely collected cancer registry and maternity data in Scotland. METHODS: We conducted a cross-sectional study of 4108 women aged ≤ 50 years with primary breast cancer diagnosed between 2009 and 2016 linked to maternity data. Molecular subtypes of breast cancer were defined using immunohistochemistry (IHC) tumour markers, oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), and tumour grade. Age-adjusted polytomous logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association of number of births, age at first birth and time since last birth with IHC-defined breast cancer subtypes. Luminal A-like was the reference compared to luminal B-like (HER2−), luminal B-like (HER2+), HER2-overexpressed and triple-negative breast cancer (TNBC). RESULTS: Mean (SD) for number of births, age at first birth and time since last birth was 1.4 (1.2) births, 27.2 (6.1) years and 11.0 (6.8) years, respectively. Luminal A-like was the most common subtype (40%), while HER2-overexpressed and TNBC represented 5% and 15% of cases, respectively. Larger numbers of births were recorded among women with HER2-overexpressed and TNBC compared with luminal A-like tumours (> 3 vs 0 births, OR 1.87, 95%CI 1.18–2.96; OR 1.44, 95%CI 1.07–1.94, respectively). Women with their most recent birth > 10 years compared to < 2 years were less likely to have TNBC tumours compared to luminal A-like (OR 0.63, 95%CI 0.41–0.97). We found limited evidence for differences by subtype with age at first birth. CONCLUSION: Number of births and time since last birth differed by molecular subtypes of breast cancer among women aged ≤ 50 years. Analyses using linked routine electronic medical records by molecularly defined tumour pathology data can be used to investigate the aetiology and prognosis of cancer

The effectiveness of non-pharmaceutical interventions in reducing SARS-CoV-2 transmission and COVID-19 incidence and mortality:systematic review and meta-analysis

OBJECTIVE: To review the evidence on the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline, Embase, CINAHL, Biosis, Joanna Briggs, Global Health, and World Health Organization COVID-19 database (preprints). ELIGIBILITY CRITERIA FOR STUDY SELECTION: Observational and interventional studies that assessed the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality. MAIN OUTCOME MEASURES: The main outcome measure was incidence of covid-19. Secondary outcomes included SARS-CoV-2 transmission and covid-19 mortality. DATA SYNTHESIS: DerSimonian Laird random effects meta-analysis was performed to investigate the effect of mask wearing, handwashing, and physical distancing measures on incidence of covid-19. Pooled effect estimates with corresponding 95% confidence intervals were computed, and heterogeneity among studies was assessed using Cochran’s Q test and the I(2) metrics, with two tailed P values. RESULTS: 72 studies met the inclusion criteria, of which 35 evaluated individual public health measures and 37 assessed multiple public health measures as a “package of interventions.” Eight of 35 studies were included in the meta-analysis, which indicated a reduction in incidence of covid-19 associated with handwashing (relative risk 0.47, 95% confidence interval 0.19 to 1.12, I(2)=12%), mask wearing (0.47, 0.29 to 0.75, I(2)=84%), and physical distancing (0.75, 0.59 to 0.95, I(2)=87%). Owing to heterogeneity of the studies, meta-analysis was not possible for the outcomes of quarantine and isolation, universal lockdowns, and closures of borders, schools, and workplaces. The effects of these interventions were synthesised descriptively. CONCLUSIONS: This systematic review and meta-analysis suggests that several personal protective and social measures, including handwashing, mask wearing, and physical distancing are associated with reductions in the incidence covid-19. Public health efforts to implement public health measures should consider community health and sociocultural needs, and future research is needed to better understand the effectiveness of public health measures in the context of covid-19 vaccination. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020178692

Appraising the causal role of risk factors in coronary artery disease and stroke:A systematic review of Mendelian Randomization studies

BACKGROUND Mendelian randomization (MR) offers a powerful approach to study potential causal associations between exposures and health outcomes by using genetic variants associated with an exposure as instrumental variables. In this systematic review, we aimed to summarize previous MR studies and to evaluate the evidence for causality for a broad range of exposures in relation to coronary artery disease and stroke. METHODS AND RESULTS MR studies investigating the association of any genetically predicted exposure with coronary artery disease or stroke were identified. Studies were classified into 4 categories built on the significance of the main MR analysis results and its concordance with sensitivity analyses, namely, robust, probable, suggestive, and insufficient. Studies reporting associations that did not perform any sensitivity analysis were classified as nonevaluable. We identified 2725 associations eligible for evaluation, examining 535 distinct exposures. Of them, 141 were classified as robust, 353 as probable, 110 as suggestive, and 926 had insufficient evidence. The most robust associations were observed for anthropometric traits, lipids, and lipoproteins and type 2 diabetes with coronary artery; disease and clinical measurements with coronary artery disease and stroke; and thrombotic factors with stroke. CONCLUSIONS Despite the large number of studies that have been conducted, only a limited number of associations were supported by robust evidence. Approximately half of the studies reporting associations presented an MR sensitivity analysis along with the main analysis that further supported the causality of associations. Future research should focus on more thorough assessments of sensitivity MR analyses and further assessments of mediation effects or nonlinearity of associations

Follow-up care after treatment for prostate cancer:evaluation of a supported self-management and remote surveillance programme

BackgroundAlternative models of cancer follow-up care are needed to ameliorate pressure on services and better meet survivors’ long-term needs. This paper reports an evaluation of a service improvement initiative for the follow-up care of prostate cancer patients based on remote monitoring and supported self-management.MethodsThis multi-centred, historically controlled study compared patient reported outcomes of men experiencing the new Programme with men experiencing a traditional clinic appointment model of follow-up care, who were recruited in the period immediately prior to the introduction of the Programme. Data were collected by self-completed questionnaires, with follow up measurement at four and eight months post-baseline. The primary outcome was men’s unmet survivorship needs, measured by the Cancer Survivors’ Unmet Needs Survey. Secondary outcomes included cancer specific quality of life, psychological wellbeing and satisfaction with care. The analysis was intention to treat. Regression analyses were conducted for outcomes at each time point separately, controlling for pre-defined clinical and demographic variables. All outcome analyses are presented in the paper. Costs were compared between the two groups.ResultsSix hundred and twenty-seven men (61%) were consented to take part in the study (293 in the Programme and 334 in the comparator group.) Regarding the primary measure of unmet survivorship needs, 25 of 26 comparisons favoured the Programme, of which 4 were statistically significant. For the secondary measures of activation for self-management, quality of life, psychological well-being and lifestyle, 20 of 32 comparisons favoured the Programme and 3 were statistically significant. There were 22 items on the satisfaction with care questionnaire and 13 were statistically significant. Per participant costs (British pounds, 2015) in the 8 month follow up period were slightly lower in the programme than in the comparator group (£289 versus £327). The Programme was acceptable to patients.ConclusionThe Programme is shown to be broadly comparable to traditional follow-up care in all respects, adding to evidence of the viability of such models

Follow-up care after treatment for prostate cancer: protocol for an evaluation of a nurse-led supported self-management and remote surveillance programme

Background: As more men survive a diagnosis of prostate cancer, alternative models of follow-up care that address men’s enduring unmet needs and are economical to deliver are needed. This paper describes the protocol for an ongoing evaluation of a nurse-led supported self-management and remote surveillance programme implemented within the secondary care setting. Methods/design: The evaluation is taking place within a real clinical setting, comparing the outcomes of men enrolled in the Programme with the outcomes of a pre-service change cohort of men, using a repeated measures design. Men are followed up at four and eight months post recruitment on a number of outcomes, including quality of life, unmet need, psychological wellbeing and activation for self-management. An embedded health economic analysis and qualitative evaluation of implementation processes are being undertaken. Discussion: The evaluation will provide important information regarding the effectiveness, cost effectiveness and implementation of an integrated supported self-management follow-up care pathway within secondary care.</p