Imputing pre-diagnosis health behaviour in cancer registry data and investigating its relationship with oesophageal cancer survival time

Background As oesophageal cancer has short survival, it is likely pre-diagnosis health behaviours will have carry-over effects on post-diagnosis survival times. Cancer registry data sets do not usually contain pre-diagnosis health behaviours and so need to be augmented with data from external health surveys. A new algorithm is introduced and tested to augment cancer registries with external data when one-to-one data linkage is not available. Methods The algorithm is to use external health survey data to impute pre-diagnosis health behaviour for cancer patients, estimate misclassification errors in these imputed values and then fit misclassification corrected Cox regression to quantify the association between pre-diagnosis health behaviour and post-diagnosis survival. Data from US cancer registries and a US national health survey are used in testing the algorithm. Results It is demonstrated that the algorithm works effectively on simulated smoking data when there is no age confounding. But age confounding does exist (risk of death increases with age and most health behaviours change with age) and interferes with the performance of the algorithm. The estimate of the hazard ratio (HR) of pre-diagnosis smoking was HR = 1.32 (95% CI 0.82,2.68) with HR = 1.93 (95% CI 1.08,7.07) in the squamous cell sub-group and pre-diagnosis physical activity was protective of survival with HR = 0.25 (95% CI 0.03, 0.81). But the method failed for less common behaviours (such as heavy drinking). Conclusions Further improvements in the I2C2 algorithm will permit enrichment of cancer registry data through imputation of new variables with negligible risk to patient confidentiality, opening new research opportunities in cancer epidemiology.

Dotting the “i” of Interoperability in FAIR Cancer-Registry Data Sets

To conform to FAIR principles, data should be findable, accessible, interoperable, and reusable. Whereas tools exist for making data findable and accessible, interoperability is not straightforward and can limit data reusability. Most interoperability-based solutions address semantic description and metadata linkage, but these alone are not sufficient for the requirements of inter-comparison of population-based cancer data, where strict adherence to data-rules is of paramount importance. Ontologies, and more importantly their formalism in description logics, can play a key role in the automation of data-harmonization processes predominantly via the formalization of the data validation rules within the data-domain model. This in turn leads to a potential quality metric allowing users or agents to determine the limitations in the interpretation and comparability of the data. An approach is described for cancer-registry data with practical examples of how the validation rules can be modeled with description logic. Conformance of data to the rules can be quantified to provide metrics for several quality dimensions. Integrating these with metrics derived for other quality dimensions using tools such as data-shape languages and data-completion tests builds up a data-quality context to serve as an additional component in the FAIR digital object to support interoperability in the wider sense.

Comparison of methods to classify ADRD in claims and cancer registry data

Alzheimer’s disease and related dementias(ADRD) affects 10.3% of older Americans (65+), among these 15-30% go on to be diagnosed with cancer. The highest burden of ADRD is experienced by Latino/a (12.2%) and African-American (13.8%) older adults. Older patients with pre-existing ADRD are less likely to receive guideline-concordant cancer care due to lack of consideration of cognitive status, and underestimation of ADRD diagnosis is an issue in secondary data. Our study compares two validated algorithms for classifying ADRD in a sample of cancer patients, the NCI-Charlson and CMS-Chronic Conditions Warehouse (CCW) index. We used existing claims from NCI’s SEER-Medicare linked database (2004-2013, N=37,932). Patients were selected based on cancer diagnosis at any stage with at least 36 months of data prior to diagnosis to identify ADRD. We analyzed breast, lung, prostate, cervix, head & neck(HNC), and colorectal(CRC) cancers(CA). We found a prevalence of 2.8% (9549 cases of ADRD+CA) using the NCI-index compared with a prevalence of 5.6% (18989 cases) with the CCW-index. ADRD+CA numbers differed significantly in all cancers for all races, however, we observed the greatest magnitude of difference among Latino/a and African-American patients. The NCI index significantly underestimated prevalence compared with the CCW: 1.21% vs 3.28% Breast; 2.29% vs 4.60% CRC; 2.88% vs 6.44% Lung; 1.36% vs 8.62% Prostate, and 4.21% vs 11.61% HNC. Our findings suggest a need to develop validated algorithms for classification, using an evidence-base generated by incorporating information and decision-making theories from the expertise of clinicians currently diagnosing ADRD using clinical assessments in diverse populations.

Differences in Uveal Melanoma Age-Standardized Incidence Rates in Two Eastern States of Australia Are Driven by Differences in Rurality and Ultraviolet Radiation

Uveal melanoma (UM) is the second-most-common melanoma in humans and has a high age-standardized incidence rate (ASR) in Australia. Regional patterns of UM ASRs in Australia are unknown. The aim of this study was to determine and compare UM ASRs in two geographically disparate eastern states, Queensland (QLD) and Victoria (VIC), by using cancer registry data that was obtained from 2001 to 2013. World-standardized UM ASRs and incidence-rate ratios (IRRs) were calculated. Higher UM ASR was also observed in anterior UM compared to posterior UM ASR. UM ASR remained unchanged from 2001 to 2013 in QLD but decreased in VIC. A south-to-north latitude trend in UM ASR along the east of Australia is weakly evident, and rural populations have higher UM ASRs than major city populations in both states. Differences in ultraviolent radiation (UVR) susceptibility, indigenous populations, social behaviours, chemical exposure, and socioeconomic status could all be contributing to differences in UM rates between QLD and VIC and between rural compared to major city areas. It is possible that a minority of cases in QLD and VIC might be prevented by sun-protective behaviours. This is important, because these findings suggest that QLD, which is already known to have one of the highest cutaneous melanoma (CM) ASRs in the world, also has one of the highest UM ASRs.

Excess Mortality by Multimorbidity, Socioeconomic, and Healthcare Factors, amongst Patients Diagnosed with Diffuse Large B-Cell or Follicular Lymphoma in England

(1) Background: Socioeconomic inequalities of survival in patients with lymphoma persist, which may be explained by patients’ comorbidities. We aimed to assess the association between comorbidities and the survival of patients diagnosed with diffuse large B-cell (DLBCL) or follicular lymphoma (FL) in England accounting for other socio-demographic characteristics. (2) Methods: Population-based cancer registry data were linked to Hospital Episode Statistics. We used a flexible multilevel excess hazard model to estimate excess mortality and net survival by patient’s comorbidity status, adjusted for sociodemographic, economic, and healthcare factors, and accounting for the patient’s area of residence. We used the latent normal joint modelling multiple imputation approach for missing data. (3) Results: Overall, 15,516 and 29,898 patients were diagnosed with FL and DLBCL in England between 2005 and 2013, respectively. Amongst DLBCL and FL patients, respectively, those in the most deprived areas showed 1.22 (95% confidence interval (CI): 1.18–1.27) and 1.45 (95% CI: 1.30–1.62) times higher excess mortality hazard compared to those in the least deprived areas, adjusted for comorbidity status, age at diagnosis, sex, ethnicity, and route to diagnosis. (4) Conclusions: Deprivation is consistently associated with poorer survival among patients diagnosed with DLBCL or FL, after adjusting for co/multimorbidities. Comorbidities and multimorbidities need to be considered when planning public health interventions targeting haematological malignancies in England.

Cancer in adolescents and young adults in Japan: epidemiology and cancer strategy

According to national cancer registry data in Japan, approximately 20,000 adolescents and young adults (AYAs, age 15–39 years) are newly diagnosed with cancer each year. Improvements in treatment and care for AYAs with cancer are included in the Phase Three Basic Plan to Promote Cancer Control Programs in Japan. This article reviews current cancer incidence and survival for AYAs with cancer in Japan using population-based cancer registry data. Mortality data through 2019 from the Vital Statistics of Japan are also described. Encouragingly, the 5-year survival probability for AYA cancers has continued to improve, in parallel with childhood cancers, and the mortality rate has decreased. There has been increasing attention to these vulnerable patients and improved partnerships and collaboration between adult and pediatric oncology; however, obstacles to the care of this population still exist at multiple levels. These obstacles relate to specific areas: research efforts and enrollment in clinical trials on AYA malignancies, AYA-specific psychosocial support such as education, financial support, and oncofertility care, and cancer care systems. It is important for Japanese oncologists, health care providers, and health policy makers to recognize that the AYA population remains vulnerable and still have unmet needs.

Sociodemographic and Geographic Disparities of Prostate Cancer Treatment Delay in Tennessee: A Population-Based Study

The relationship of social determinants of health, Appalachian residence, and prostate cancer treatment delay among Tennessee adults is relatively unknown. We used multivariate logistic regression on 2005–2015 Tennessee Cancer Registry data of adults aged ≥18 diagnosed with prostate cancer. The outcome of treatment delay was more than 90 days without surgical or nonsurgical intervention from date of diagnosis. Social determinants in the population-based registry were race (White, Black, Other) and marital status (single, married, divorced/separated, widow/widower). Tennessee residence was classified as Appalachian versus non-Appalachian (urban/rural). Covariates include age at diagnosis (18–54, 54–69, ≥70), health insurance type (none, public, private), derived staging of cancer (localized, regional, distant), and treatment type (non-surgical/surgical). We found that Black and divorced/separated patients had 32% (95% confidence interval [CI]: 1.22–1.42) and 15% (95% CI: 1.01–1.31) increased odds to delay prostate cancer treatment. Patients were at decreased odds of treatment delay when living in an Appalachian county, both urban (odds ratio [OR] = 0.89, 95% CI: 0.82–0.95) and rural (OR = 0.83, 95% CI: 0.78–0.89), diagnosed at ≥70 (OR = 0.59, 95% CI: 0.53–0.66), and received surgical intervention (OR = 0.72, 95% CI: 0.68–0.76). Our study was among the first to comprehensively examine prostate cancer treatment delay in Tennessee, and while we do not make clinical recommendations, there is a critical need to further explore the unique factors that may propagate disparities. Prostate cancer treatment delay in Black patients may be indicative of ongoing health and access disparities in Tennessee, which may further affect quality of life and survivorship among this racial group. Divorced/separated patients may need tailored interventions to improve social support.