4.8.1 Results in context
Cancers in children and young adults are rare. In Yorkshire, as reported elsewhere, incidence is higher in TYA compared to children. Since the early 1990s cancer incidence in children in the UK has increased by 15%, the incidence rate for cases diagnosed 2010-2012 was 157 per million [11]. This compared with an incidence rate of 138 per million in this study based on all cases diagnosed from 1990-2011. Nationally for TYA (aged 15-24 years) incidence rates have increased by 33% since the early 1990s. National rates
have been estimated to be 298 per million in 2010-2012 [15]. For England, crude incidence rates for the 13-24 year age group were estimated to be 298 per million for 2013-2015 [87]. Neither of these rates included the 25-29 year age group that are included in this thesis, therefore direct comparison between rates is difficult. In Yorkshire for 15-29 year olds the incidence rate from 1990- 2011 was 202 per million.
For the study cohort overall 5-year survival was 76% for children and 78% for TYA, with both age groups showing significant increases in survival over time. National 5-year survival for children diagnosed 2006-2010 was 82% [11] and for TYA (15-24 years) diagnosed 2001-2005 was 81% [15]. In general, there is no evidence to suggest that incidence and survival rates and trends are different in Yorkshire compared to national data.
Survival varies by diagnostic group and from the study data included in this thesis for most diagnostic groups there were sufficient numbers to examine survival trends. Although for some diagnostic groups, bone tumours, soft tissue sarcoma, neuroblastoma and renal tumours, several years’ data had to be aggregated and limited temporal trends analysis could be conducted.
The first step in determining if statistical cure is an appropriate assumption is to graphically check if the survival curves level off and plateau during follow-up [28]. For most diagnostic groups this seems a reasonable assumption, although the length of follow-up needed may vary by diagnostic group, for example longer follow-up may be needed for CNS tumours. Further examination of cure models by diagnostic group are presented in Chapter 5. Leukaemia is the most commonly diagnosed cancer within children and acute lymphoblastic leukaemia (ALL) accounts for 80% of all leukaemias [10]. This subgroup is included in a detailed analysis examining statistical cure and relapse by clinical
characteristics, including further linkage to cytogenetic risk factor data (results also presented in Chapter 5).
Linkage to HES admission data were available for 90% of the study cohort. This is comparable to other cancer registry linked HES admission studies [240, 281, 282]. There were some differences in individuals linked and not linked to HES and results based on hospital admissions need to be interpreted with this in mind (See Section 4.8.2 below and further discussion in Chapter 9). HES
admissions will be used as a proxy for long-term morbidity in Chapters 6 and 8 to quantify and assess the late effects of respiratory and cardiovascular disease in childhood and young adult cancer survivors.
4.8.2 Strengths and limitations
Key strength of the data used throughout this thesis are that the data are population-based and includes detailed patient, tumour and treatment related factors. The full 0-29 year age range were included, compared to other studies that may not include this full age range. No data were available for those aged 30-39 years at diagnosis so limited comparisons with studies based on the TYA age range of 15-39 years (such as TYACCS) were possible. However this thesis does provide essential intelligence on long-term outcomes for this understudied TYA group.
The late effects for this cohort were based upon hospital admission data providing an objective outcome measure compared to other studies based on self-reported questionnaires, which may suffer from recall bias and non- response, or studies based on clinical assessments, which may pick up non- symptomatic conditions and are generally single-centred.
There are several limitations to be acknowledged. Firstly given the rarity of certain diagnostic groups, limited analysis is possible due to small numbers. For example examining trends in survival for each diagnostic group a threshold of a minimum of 50 cases was used to ensure sufficient number to enable robust estimation of survival by age groups and time period. While this is an arbitrary threshold it is in line with national recommendations from PHE [250].
Stage data were not available for all diagnostic groups and even for the diagnostic groups with sufficient stage information it was still missing for up to 40% of cases. This has implications for inclusion in statistical models as a potential confounder. However, as discussed in the methods (Section 3.5.3), variables other than stage were selected based on the relevant DAGs.
Linkage to HES was only available for 90% of the study population and analysis of those linked and not linked showed difference by patient characteristics. This means that certain groups may be under-represented in the analysis of late
effects, including those diagnosed with germ cell tumours, who also have high survival rates, and those aged 25-29 years at diagnosis. This is a limitation of this study. However, there were no differences in the linkage rate by
deprivation. The linkage rate was lower for those diagnosed in the earlier time period as HES data were only available from 1997 onwards so for these patients no admissions around the time of diagnosis and treatment were available, only longer-term admissions. Hospital admissions were used as the basis to evaluate long-term morbidity and for those not linked to any HES admissions it is unclear if no late effects were observed in this group as a result of actually having no long-term admissions or as a results of linkage errors and therefore these admissions were not captured. This means that the estimates of long-term morbidity may be an underestimation of the true burden of disease. Further issues around potential linkage errors and the implications of this are discussed further in Chapter 9, Section 9.4.1. It was observed that 60% of 5- year survivors had at least one admission 5-years post diagnosis. Reassuringly the linkage rate for these data are similar to other national studies based on cancer registry linked HES data [240, 281, 282] and compare favourably with studies based on questionnaire responses which typically have lower response rates, for example the BBCSS had a response rate of 70% [80].
4.8.3 Summary
This chapter provides a detailed description of the registry and linked hospital admission data that were used in the analysis presented in Chapters 5-8. Chapter 5 includes further detailed modelling of statistical cure. HES
admissions will be used as a proxy for morbidity in Chapters 6 and 8 to quantify and assess the late effects of respiratory and cardiovascular disease in
childhood and young adult cancer survivors. Chapter 7 includes investigation of subsequent tumours based on cancer registration data. Table 3.6 showed the different study populations included in each chapter and the descriptive
characteristics of these groups are provided at the start of each relevant chapter in relation to the outcome of interest.