On the prediction and projection of cancer survival

Cancer survival is a key metric for monitoring improvement in awareness, early diagnosis and access to effective treatments for cancer patients. For the majority of cancers, survival has been increasing for a number of decades, as a result of successful health policies and the availability of more effective treatment. Nevertheless, there is an unavoidable delay between policy implementation and impact. In parallel, the measure of survival requires follow-up information, adding to the delay in quantifying health benefits. Predictions of cancer survival for cohorts of patients most recently diagnosed could help fill the gap in our knowledge of the likely effects of cancer policies. In this thesis, I modelled the excess hazard of death as a function of predictors available in linked cancer registry data in the UK. These include age, stage and year of diagnosis, levels of deprivation, type of diagnosis, and access to curative treatment. In such contexts, selecting the form of the model, the predictors, the shape of their effects, and potential interactive effects is challenging. Several model selection strategies are compared and their performance assessed in simulations. I provide practical guidelines for the modelling of the excess hazard of death, in particular in relation to cancer lethality, model complexity and impact of model mis-specification. Besides, these multi-variable regression models offer opportunities for predicting cancer-related death rate, for cohorts of patients most recently diagnosed, and for whom follow-up is not yet available. Along with model selection algorithms, I explore strategies based on information criteria and model averaging. Inference is therefore conditional on a pool of models of equivalent support, rather than a uniquely selected model. Advantages include absence of multiple testing, and allowance for model selection uncertainty in inference. Finally, a measure of explained variation, RE, is extended to the relative survival data setting. It is part of the model validation toolkit, and can provide estimates of how much variation in excess mortality due to cancer is explained by the models, and the variables that compose them. There are several methodological assets from the work presented here. First, excess hazard model selection is well formalised. Furthermore, the way RE is adapted to the relative survival data setting will most certainly nurture ideas for the adaptation of other validation tools, commonly used in prognosis research. Lastly, multi-model inference using model averaging is paving the way for the utilisation of ensemble learning in the prediction of excess hazard of death due to cancer. Scenario modelling is a public health application that naturally follows the work done in this PhD thesis. With well-crafted set of predictive models, simulated scenarios can be designed to identify areas for improvement in policy, prevention or treatment. Those generating largest increase in survival can lead to actual recommendations. Methodological advances and public health go hand in hand here. This work emphasises the importance of developing, assessing, and validating excess hazard models. It offers a toolkit so that accurate survival predictions help design effective policies

Cancer survival differences between South Asians and non-South Asians of England in 1986-2004, accounting for age at diagnosis and deprivation.

BACKGROUND: South Asian migrants show lower cancer incidence than their host population in England for most major cancers. We seek to study the ethnic differences in survival from cancer. METHODS: We described and modelled the effect of ethnicity, time, age and deprivation on survival for the five most incident cancers in each sex in South Asians in England between 1986 and 2004 using national cancer registry data. South Asian ethnicity was flagged using the validated name-recognition algorithm SANGRA (South Asian Names and Group Recognition Algorithm). RESULTS: We observed survival advantage in South Asians in earlier periods. This ethnic gap either remained constant or narrowed over time. By 2004, age-standardised net survival was comparable for all cancers except three in men, where South Asians had higher survival 5 years after diagnosis: colorectal (58.9% vs 53.6%), liver (15.0% vs 9.4%) and lung (15.9% vs 9.3%). Compared with non-South Asians, South Asians experienced a slower increase in breast and prostate cancer survival, both cancers associated with either a screening programme or an early diagnosis test. We did not find differential patterns in survival by deprivation between both ethnicities. CONCLUSIONS: Considering recent survival trends, appropriate action is required to avoid deficits in cancer survival among South Asians in the near future

The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study (vol 21, pg 1023, 2020)

Background Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types. Methods In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15–84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data. Findings We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9–9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266–295) and 344 (329–358) additional deaths. For colorectal cancer, we estimate 1445 (1392–1591) to 1563 (1534–1592) additional deaths, a 15·3–16·6% increase; for lung cancer, 1235 (1220–1254) to 1372 (1343–1401) additional deaths, a 4·8–5·3% increase; and for oesophageal cancer, 330 (324–335) to 342 (336–348) additional deaths, 5·8–6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291–3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204–63 229 years. Interpretation Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer

Contrasting effects of comorbidities on emergency colon cancer diagnosis: a longitudinal data-linkage study in England

BACKGROUND: One in three colon cancers are diagnosed as an emergency, which is associated with worse cancer outcomes. Chronic conditions (comorbidities) affect large proportions of adults and they might influence the risk of emergency presentations (EP). METHODS: We aimed to evaluate the effect of specific pre-existing comorbidities on the risk of colon cancer being diagnosed following an EP rather than through non-emergency routes. The cohort study included 5745 colon cancer patients diagnosed in England 2005-2010, with individually-linked cancer registry, primary and secondary care data. In addition to multivariable analyses we also used potential-outcomes methods. RESULTS: Colon cancer patients with comorbidities consulted their GP more frequently with cancer symptoms during the pre-diagnostic year, compared with non-comorbid cancer patients. EP occurred more frequently in patients with 'serious' or complex comorbidities (diabetes, cardiac and respiratory diseases) diagnosed/treated in hospital during the years pre-cancer diagnosis (43% EP in comorbid versus 27% in non-comorbid individuals; multivariable analysis Odds Ratio (OR), controlling for socio-demographic factors and symptoms: men OR = 2.40; 95% CI 2.0-2.9 and women OR = 1.98; 95% CI 1.6-2.4. Among women younger than 60, gynaecological (OR = 3.41; 95% CI 1.2-9.9) or recent onset gastro-intestinal conditions (OR = 2.84; 95% CI 1.1-7.7) increased the risk of EP. In contrast, primary care visits for hypertension monitoring decreased EPs for both genders. CONCLUSIONS: Patients with comorbidities have a greater risk of being diagnosed with cancer as an emergency, although they consult more frequently with cancer symptoms during the year pre-cancer diagnosis. This suggests that comorbidities may interfere with diagnostic reasoning or investigations due to 'competing demands' or because they provide 'alternative explanations'. In contrast, the management of chronic risk factors such as hypertension may offer opportunities for earlier diagnosis. Interventions are needed to support the diagnostic process in comorbid patients. Appropriate guidelines and diagnostic services to support the evaluation of new or changing symptoms in comorbid patients may be useful

External perceptions of successful university brands

Branding in universities has become an increasingly topical issue, with some institutions committing substantial financial resources to branding activities. The particular characteristics of the sector present challenges for those seeking to build brands and it therefore seems to be timely and appropriate to investigate the common approaches of those institutions perceived as having successful brands. This study is exploratory in nature, seeking to investigate how successfully UK universities brand themselves, whether they are distinct and if the sector overall communicates effectively. This is approached through examining the perspective of opinion formers external to universities but closely involved with the sector – a key stakeholder group in UK higher education Overall, the research’s exploratory nature aims to further the debate on effective branding in UK higher education. The findings and conclusions identify some issues surrounding university branding activity; most UK universities were considered to be distinct from one another, but few were seen to have real fully formed brands. Although a number of institutions that were seen as having more ‘successful’ brands were identified, it was argued that whilst many UK universities communicate their brand well enough to key stakeholders, they fail to consistently do this across all audiences. It was also suggested that UK universities may concentrate on areas of perceived immediate strategic importance (in terms of branding) to an extent where others are neglected

Persistent inequalities in unplanned hospitalisation among colon cancer patients across critical phases of their care pathway, England, 2011-13.

BACKGROUND: Reducing hospital emergency admissions is a key target for all modern health systems. METHODS: We analysed colon cancer patients diagnosed in 2011-13 in England. We screened their individual Hospital Episode Statistics records in the 90 days pre-diagnosis, the 90 days post-diagnosis, and the 90 days pre-death (in the year following diagnosis), for the occurrence of hospital emergency admissions (HEAs). RESULTS: Between a quarter and two thirds of patients experience HEA in the three 90-day periods examined: pre-diagnosis, post-diagnosis and before death. Patients with tumour stage I-III from more deprived backgrounds had higher proportions of HEAs than less deprived patients during all studied periods. This remains even after adjusting for differing distributions of risk factors such as age, sex, comorbidity and stage at diagnosis. CONCLUSIONS: Although in some cases HEAs might be unavoidable or even appropriate, the proportion of HEAs varies by socioeconomic status, even after controlling for the usual patient factors, suggestive of remediable causes of excess emergency healthcare utilisation in patients belonging to higher deprivation groups. Future inquiries should address the potential role of clinical complications, sub-optimal healthcare administration, premature discharge or a lack of social support as potential explanations for these patterns of inequality

Exploring rationales for branding a university: Should we be seeking to measure branding in UK universities?

Although branding is now widespread among UK universities, the application of branding principles in the higher education sector is comparatively recent and may be controversial for internal audiences who question its suitability and efficiency. This paper seeks to investigate how and whether the effectiveness of branding activity in the higher education sector should be evaluated and measured, through exploratory interviews with those who often drive it; UK University marketing professionals. Conclusions suggest that university branding is inherently complex and therefore application of commercial approaches may be over simplistic. Whilst marketing professionals discuss challenges they do not necessarily have a consistent view of the objectives of branding activity although all were able to clearly articulate branding objectives for their university, including both qualitative and, to some extent, quantitative metrics. Some measures of the real value of branding activity are therefore suggested but a key debate is perhaps whether the objectives and role of branding in higher education needs to be clarified, and a more consistent view of appropriate metrics reached? Various challenges in implementing branding approaches are also highlighted

Summarizing and communicating on survival data according to the audience: a tutorial on different measures illustrated with population-based cancer registry data

Aurélien Belot, Aminata Ndiaye, Miguel-Angel Luque-Fernandez, Dimitra-Kleio Kipourou, Camille Maringe, Francisco Javier Rubio, Bernard Rachet Cancer Survival Group, Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK Abstract: Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. In the overall survival setting, we describe the overall survival probability, the conditional survival probability and the restricted mean survival time (restricted to a prespecified time window). In the relative survival setting, we describe the net survival probability, the conditional net survival probability, the restricted mean net survival time, the crude probability of death due to each cause and the number of life years lost due to each cause over a prespecified time window. These measures describe survival data either on a probability scale or on a timescale. The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15–80 years old diagnosed with colon cancer in 2001–2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use. Keywords: survival, competing risks, relative survival setting, conditional survival, restricted mean survival time, net survival, crude probability of death, number of life years los

Persistent inequalities in 90-day colon cancer mortality: an English cohort study.

BACKGROUND: Variation in colon cancer mortality occurring shortly after diagnosis is widely reported between socio-economic status (SES) groups: we investigated the role of different prognostic factors in explaining variation in 90-day mortality. METHODS: National cancer registry data were linked with national clinical audit data and Hospital Episode Statistics records for 69 769 adults diagnosed with colon cancer in England between January 2010 and March 2013. By gender, logistic regression was used to estimate the effects of SES, age and stage at diagnosis, comorbidity and surgical treatment on probability of death within 90 days from diagnosis. Multiple imputations accounted for missing stage. We predicted conditional probabilities by prognostic factor patterns and estimated the effect of SES (deprivation) from the difference between deprivation-specific average predicted probabilities. RESULTS: Ninety-day probability of death rose with increasing deprivation, even after accounting for the main prognostic factors. When setting the deprivation level to the least deprived group for all patients and keeping all other prognostic factors as observed, the differences between deprivation-specific averaged predicted probabilities of death were greatly reduced but persisted. Additional analysis suggested stage and treatment as potential contributors towards some of these inequalities. CONCLUSIONS: Further examination of delayed diagnosis, access to treatment and post-operative care by deprivation group may provide additional insights into understanding deprivation disparities in mortality

Cancer symptom awareness and barriers to symptomatic presentation in England – Are we clear on cancer?

Background: Low cancer awareness may contribute to delayed diagnosis and poor cancer survival. We aimed to quantify socio-demographic differences in cancer symptom awareness and barriers to symptomatic presentation in the English population. Methods: Using a uniquely large data set (n=49?270), we examined the association of cancer symptom awareness and barriers to presentation with age, gender, marital status and socio-economic position (SEP), using logistic regression models to control for confounders. Results: The youngest and oldest, the single and participants with the lowest SEP recognised the fewest cancer symptoms, and reported most barriers to presentation. Recognition of nine common cancer symptoms was significantly lower, and embarrassment, fear and difficulties in arranging transport to the doctor’s surgery were significantly more common in participants living in the most deprived areas than in the most affluent areas. Women were significantly more likely than men to both recognise common cancer symptoms and to report barriers. Women were much more likely compared with men to report that fear would put them off from going to the doctor. Conclusions: Large and robust socio-demographic differences in recognition of some cancer symptoms, and perception of some barriers to presentation, highlight the need for targeted campaigns to encourage early presentation and improve cancer outcomes