Region-based analyses of existing genome-wide association studies identifies novel potential genetic susceptibility regions for glioma.

PURPOSE: Glioma is a rare and debilitating brain cancer with one of the lowest cancer survival rates. Genome-wide association studies have identified 34 genetic susceptibility regions. We sought to discover novel susceptibility regions using approaches which test groups of contiguous genetic markers simultaneously. PATIENTS AND METHODS: We analyzed data from three independent glioma studies of European ancestry, GliomaScan (1,316 cases/1,293 controls), AGOG (560 cases/2,237 controls), and GICC (4,000 cases/2,411 controls), using the machine-learning algorithm DEPTH and a region-based regression method based on the generalized Berk-Jones (GBJ) statistic, to assess the association of glioma with genomic regions by glioma type and sex. Summary statistics from the UCSF/Mayo Clinic study were used for independent validation. We conducted a meta-analysis using GliomaScan, AGOG, GICC and UCSF/Mayo. RESULTS: We identified 11 novel candidate genomic regions for glioma risk common to multiple studies. Two of the 11 regions, 16p13.3 containing RBFOX1 and 1p36.21 containing PRDM2, were significantly associated with female and male glioma risk respectively, based on results of the meta-analysis. Both regions have been previously linked to glioma tumor progression. Three of the 11 regions contain neurotransmitter receptor genes (7q31.33 GRM8, 5q35.2 DRD1, 15q13.3 CHRNA7). CONCLUSIONS: Our region-based approach identified 11 genomic regions that suggest association with glioma risk of which two regions, 16p13.3 and 1p36.21, warrant further investigation as genetic susceptibility regions for female and male risk respectively. Our analyses suggest that genetic susceptibility to glioma may differ by sex and highlights the possibility that synapse-related genes play a role in glioma susceptibility.

The Medicines Intelligence Data Platform: A Population-Based Data Resource From New South Wales, Australia.

BACKGROUND: The Medicines Intelligence (MedIntel) Data Platform is an anonymised linked data resource designed to generate real-world evidence on prescribed medicine use, effectiveness, safety, costs and cost-effectiveness in Australia. RESULTS: The platform comprises Medicare-eligible people who are ≥18 years and residing in New South Wales (NSW), Australia, any time during 2005-2020, with linked administrative data on dispensed prescription medicines (Pharmaceutical Benefits Scheme), health service use (Medicare Benefits Schedule), emergency department visits (NSW Emergency Department Data Collection), hospitalisations (NSW Admitted Patient Data Collection) plus death (National Death Index) and cancer registrations (NSW Cancer Registry). Data are currently available to 2022, with approval to update the cohort and data collections annually. The platform includes 7.4 million unique people across all years, covering 36.9% of the Australian adult population; the overall population increased from 4.8 M in 2005 to 6.0 M in 2020. As of 1 January 2019 (the last pre-pandemic year), the cohort had a mean age of 48.7 years (51.1% female), with most people (4.4 M, 74.7%) residing in a major city. In 2019, 4.4 M people (73.3%) were dispensed a medicine, 1.2 M (20.5%) were hospitalised, 5.3 M (89.4%) had a GP or specialist appointment, and 54 003 people died. Anti-infectives were the most prevalent medicines dispensed to the cohort in 2019 (43.1%), followed by nervous system (32.2%) and cardiovascular system medicines (30.2%). CONCLUSION: The MedIntel Data Platform creates opportunities for national and international research collaborations and enables us to address contemporary clinically- and policy-relevant research questions about quality use of medicines and health outcomes in Australia and globally.

Cohort profile: understanding health service system needs for people with intellectual disability using linked data in New South Wales, Australia.

This cohort profile describes one of the largest linked datasets in the world concerning the health of people with intellectual disability. The cohort comprises a retrospective group of 100,089 individuals with intellectual disability who received disability and/or health services in New South Wales, Australia. Of these participants, 34% were female, with a median age at cohort entry of 3 years (interquartile range, 0-19). A separate comparator cohort included 455,677 individuals, matched by 5-year age group, sex, and residential postcode at a 5:1 ratio. Initial results indicate that between 2001 and 2018, people with intellectual disability experienced more than double the rate of hospitalisations (538 vs. 235 per 1,000 person-years), as well as markedly higher rates of emergency department presentations (707 vs. 379 per 1,000 person-years) and use of ambulatory mental health services (1,012 vs. 157 per 1,000 person-years), relative to the comparator cohort. The largest disparities in hospital admissions were for mental disorders, dialysis, and diseases of the nervous system and sense organs. Furthermore, individuals with intellectual disability had more than double the rate of dispensed medications found in the comparator cohort. Of these medications, 46.6% were for the treatment of nervous system conditions, as opposed to 24.7% for the comparator cohort. The mean±standard deviation age at death was 52±19 years for people with intellectual disability and 64±22 years for the comparator participants.

Cancer risk in people living with HIV and solid organ transplant recipients: a systematic review and meta-analysis.

BACKGROUND: Systematic evaluations of cancer risk in people living with HIV or AIDS (PLHIV) and solid organ transplant recipients provide unique insights into the role of the immune system in cancer development. In this systematic review and meta-analysis, we expand previous analyses of cancer risk for these two immunocompromised populations. METHODS: We considered studies published in English and listed on PubMed or Embase up to July 1, 2022. Studies were eligible for inclusion if they used population-based registries and compared cancer incidence in PLHIV or solid organ transplant recipients with the general population in the same geographical area. We extracted the number of observed site-specific cancers and expected cases and calculated meta-standardised incidence ratios for cancer within PLHIV and solid organ transplant recipients. In solid organ transplant recipients meta-standardised incidence ratios were compared by organ type. This project is registered on PROSPERO, CRD42022366679. FINDINGS: 46 studies in PLHIV and 67 in solid organ transplant recipients were included in the analysis. Meta-standardised incidence ratios for cancers associated with human papillomavirus were increased in both populations; the highest meta-standardised incidence ratio in PLHIV was anal cancer (37·28 [95% CI 23·65-58·75], I2=97·4%), and in solid organ transplant recipients was cutaneous squamous cell carcinoma (45·87 [31·70-66·38], I2=99·0%). Meta-standardised incidence ratios were significantly increased for most non-HPV viral-infection-related cancers in both populations; the highest standard incidence ratios were for Kaposi sarcoma (PLHIV: 801·52 [95% CI 200·25-3208·13], I2=100·0%; solid organ transplant recipients: 47·31 [23·09-96·95], I2=87·7%) and non-Hodgkin lymphoma (32·53 [19·64-53·87], I2=99·8%; 10·24 [8·48-12·35], I2=94·9%). Eight types of cancer with no known viral cause showed an increased risk in solid organ transplant recipients only; no cancer type showed increased risk in PLHIV only. INTERPRETATION: Cancer risk was increased for a range of infection-related cancers in both PLHIV and solid organ transplant recipients, but divergent results in these and other cancers have emerged. The cancer risk patterns probably reflect variances in the degree of impaired immunity, exposure to carcinogenic viruses, and perhaps exposure to carcinogenic immunosuppressive agents. FUNDING: US National Cancer Institute, National Institutes of Health.

Estimating the impact of bias in causal epidemiological studies: the case of health outcomes following assisted reproduction.

Researchers interested in causal questions must deal with two sources of error: random error (random deviation from the true mean value of a distribution), and bias (systematic deviance from the true mean value due to extraneous factors). For some causal questions, randomization is not feasible, and observational studies are necessary. Bias poses a substantial threat to the validity of observational research and can have important consequences for health policy developed from the findings. The current piece describes bias and its sources, outlines proposed methods to estimate its impacts in an observational study, and demonstrates how these methods may be used to inform debate on the causal relationship between medically assisted reproduction (MAR) and health outcomes, using cancer as an example. In doing so, we aim to enlighten researchers who work with observational data, especially regarding the health effects of MAR and infertility, on the pitfalls of bias, and how to address them. We hope that, in combination with the provided example, we can convince readers that estimating the impact of bias in causal epidemiologic research is not only important but necessary to inform the development of robust health policy and clinical practice recommendations.

Relative survival in patients with cancer and kidney failure.

BACKGROUND: The population with kidney failure is at increased risk of cancer and associated mortality. Relative survival can provide insight into the excess mortality, directly or indirectly, attributed to cancer in the population with kidney failure. METHODS: We estimated relative survival for people all ages receiving dialysis (n = 4089) and kidney transplant recipients (n = 3253) with de novo cancer, and for the general population with cancer in Australia and New Zealand (n = 3 043 166) over the years 1980-2019. The entire general population was the reference group for background mortality, adjusted for sex, age, calendar year and country. We used Poisson regression to quantify excess mortality ratios. RESULTS: Five-year relative survival for all-site cancer was markedly lower than that for the general population for people receiving dialysis [0.25, 95% confidence interval (CI) 0.23-0.26] and kidney transplant recipients (0.55, 95% CI 0.53-0.57). In dialysis, excess mortality was more than double (2.16, 95% CI 2.08-2.25) that of the general population with cancer and for kidney transplant recipients 1.34 times higher (95% CI 1.27-2.41). There was no difference in excess mortality from lung cancer between people with kidney failure and the general population with cancer. Comparatively, there was a significant survival deficit for people with kidney failure, compared with the general population with cancer, for melanoma, breast cancer and prostate cancers. CONCLUSION: Decreased cancer survival in kidney failure may reflect differences in multi-morbidity burden, reduced access to treatment, or greater harm from or reduced efficacy of treatments. Our findings support research aimed at investigating these hypotheses.

Transmission and Non-transmission of Melanoma From Deceased Solid Organ Donors to Transplant Recipients: Risks and Missed Opportunities.

BACKGROUND: Biovigilance concerns are in tension with the need to increase organ donation. Cancer transmission risk from donor to recipient may be overestimated, as non-transmission events are rarely reported. We sought to estimate melanoma transmission risk in deceased organ donation and identify missed opportunities for donation in an Australian cohort with high melanoma prevalence. METHODS: We used a population-based approach and linked deceased organ donors, transplant recipients, and potential donors forgone, 2010-2018, with the Central Cancer Registry (CCR), 1976-2018. We identified melanomas using ICD-O-3 classification, assessed the probability of transmission, and compared suspected melanoma history in potential donors forgone with melanoma notifications in the CCR. RESULTS: There were 9 of 993 donors with melanoma in CCR; 4 in situ low-risk and 5 invasive high-to-unacceptable risk. Four were unrecognized before donation. Of 16 transplant recipients at risk, we found 0 of 14 transmission events (2 recipients had insufficient follow-up). Of 35 of 3588 potential donors forgone for melanoma risk alone, 17 were otherwise suitable for donation; 6 of 35 had no melanoma in CCR, 2 of 35 had in situ melanomas and 9 of 35 had thin invasive melanomas (localized, ≤0.8 mm thickness). CONCLUSIONS: Our findings contribute to current evidence that suggests donors with melanomas of low metastatic potential may provide an opportunity to safely increase organ donation and so access to transplantation.

A Population-Based Family Case-Control Study of Sun Exposure and Follicular Lymphoma Risk.

BACKGROUND: Epidemiologic evidence suggests an inverse association between sun exposure and follicular lymphoma risk. METHODS: We conducted an Australian population-based family case-control study based on 666 cases and 459 controls (288 related, 171 unrelated). Participants completed a lifetime residence and work calendar and recalled outdoor hours on weekdays, weekends, and holidays in the warmer and cooler months at ages 10, 20, 30, and 40 years, and clothing types worn in the warmer months. We used a group-based trajectory modeling approach to identify outdoor hour trajectories over time and examined associations with follicular lymphoma risk using logistic regression. RESULTS: We observed an inverse association between follicular lymphoma risk and several measures of high lifetime sun exposure, particularly intermittent exposure (weekends, holidays). Associations included reduced risk with increasing time outdoors on holidays in the warmer months [highest category OR = 0.56; 95% confidence interval (CI), 0.42-0.76; Ptrend < 0.01], high outdoor hours on weekends in the warmer months (highest category OR = 0.71; 95% CI, 0.52-0.96), and increasing time outdoors in the warmer and cooler months combined (highest category OR = 0.66; 95% CI, 0.50-0.91; Ptrend 0.01). Risk was reduced for high outdoor hour maintainers in the warmer months across the decade years (OR = 0.71; 95% CI, 0.53-0.96). CONCLUSIONS: High total and intermittent sun exposure, particularly in the warmer months, may be protective against the development of follicular lymphoma. IMPACT: Although sun exposure is not recommended as a cancer control policy, confirming this association may provide insights regarding the future control of this intractable malignancy.

Sunlight, vitamin D, vitamin D receptor polymorphisms, and risk of multiple myeloma: A systematic review.

This systematic review examines the relationship with multiple myeloma (MM) risk for sunlight and vitamin D related exposures, including vitamin D supplementation, circulating 25-hydroxyvitamin D concentration, personal ultraviolet B radiation exposure, ambient solar irradiance and vitamin D receptor (VDR) gene polymorphisms We conducted a search for terms related to multiple myeloma, vitamin D, vitamin D receptor, ultraviolet radiation, sunlight, and single nucleotide polymorphism (SNP) using Ovid MEDLINE, Ovid EMBASE, Web of Science and Cochrane CENTRAL. Studies were assessed for risk of bias and quality using the RoB 2.0, ROBINS-E or Q-Genie tools. We identified 13 eligible studies: one randomised controlled trial, two cohort studies, and ten case-control studies, including one nested case-control study and one meta-analysis of genome-wide association studies. We conducted a qualitative synthesis; quantitative synthesis was not appropriate due to study heterogeneity and the small number of studies identified. There was insufficient evidence to support an effect of any sunlight or vitamin D related exposure on MM risk. No polymorphisms in VDR were found to be strongly related to risk for people of European ancestry. Of the identified studies, many had high risk of bias or were of lower quality. Few studies have investigated the association between sunlight and vitamin D related exposures and multiple myeloma risk. The scarcity of high-quality studies makes it difficult to evaluate potential effects of these exposures on MM risk. Further research is necessary to investigate the influence of vitamin D related exposures on risk of multiple myeloma..

Effectiveness of COVID-19 vaccination against COVID-19 specific and all-cause mortality in older Australians: a population based study.

Background: Few studies have examined effectiveness of COVID-19 vaccines against COVID-19 and all-cause mortality across different pandemic periods in 2022. Methods: We used linked whole-of-population data from the 2021 Australian Census, Australian Immunisation Register, death registrations and other national datasets including migration data. Among 3.8 million adults aged 65+ years and >170,000 aged care residents, we used survival analysis to estimate vaccine effectiveness (VE) against COVID-19 specific mortality and all-cause mortality, by vaccine dose and time since receipt, adjusted for age, sex and other factors. We also estimated absolute COVID-19 mortality rates. Findings: From January-May 2022 (Omicron BA.1/2), 3250 COVID-19 deaths occurred; from June-November (Omicron BA.4/5) 3185 COVID-19 deaths occurred. During January-May, VE of a 3rd COVID-19 vaccine dose within 3 months was 93% (95% CI 93-94%) whilst VE of a 2nd dose >6 months since receipt was 34% (26-42%). During June-November, VE of a 4th COVID-19 vaccine dose within 3 months was 84% (82-86%) whilst VE of a 3rd dose >6 months since receipt was 56% (50-62%). VE estimates for aged care residents were similar, but absolute risk reductions were substantially greater. During June-November 2022, for all-cause mortality, VE of a 4th dose within 3 months was 58% (56-59%) whilst VE of a 3rd dose >6 months since receipt was 19% (16-22%). Interpretations: COVID-19 vaccination is highly effective against COVID-19 mortality among older adults although effectiveness wanes with time since the last dose. Our findings emphasise the importance of continuing to administer booster doses, particularly to those at highest risk. Funding: This study was funded by the Health Economics Research Division in the Australian Government Department of Health and Aged Care.

Modifiable lifestyle risk factors and survival after diagnosis with multiple myeloma.

BACKGROUND: While remaining incurable, median overall survival for MM now exceeds 5 years. Yet few studies have investigated how modifiable lifestyle factors influence survival. We investigate whether adiposity, diet, alcohol, or smoking are associated with MM-related fatality. RESEARCH DESIGN AND METHODS: We recruited 760 incident cases of MM via cancer registries in two Australian states during 2010-2016. Participants returned questionnaires on health and lifestyle. Follow-up ended in 2020. Flexible parametric survival models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for lifestyle exposures and risk of all-cause and MM-specific fatality. RESULTS: Higher pre-diagnosis Alternative Healthy Eating Index (AHEI) scores were associated with reduced MM-specific fatality (per 10-unit score, HR = 0.84, 95%CI = 0.70-0.99). Pre-diagnosis alcohol consumption was inversely associated with MM-specific fatality, compared with nondrinkers (0.1-20 g per day, HR = 0.59, 95%CI = 0.39-0.90; >20 g per day, HR = 0.67, 95%CI = 0.40-1.13). Tobacco smoking was associated with increased all-cause fatality compared with never smoking (former smokers: HR = 1.44, 95%CI = 1.10-1.88; current smokers: HR = 1.30, 95%CI = 0.80-2.10). There was no association between pre-enrollment body mass index (BMI) and MM-specific or all-cause fatality. CONCLUSIONS: Our findings support established recommendations for healthy diets and against smoking. Higher quality diet, as measured by the AHEI, may improve survival post diagnosis with MM.

Occupational exposure to extremely low-frequency magnetic fields and follicular lymphoma risk: a family case-control study.

OBJECTIVES: We aimed to examine the relationship between occupational exposure to extremely low-frequency magnetic fields (ELF-MFs) and follicular lymphoma (FL) risk. METHODS: We conducted a family case-control study between 2011 and 2016 in Australia and included 681 cases. Controls were either a family member of cases (related (n=294), unrelated (n=179)) or were unrelated recruited for a similarly designed Australian multiple myeloma study (n=711). We obtained detailed job histories using lifetime work calendars. We assigned exposure to ELF-MFs using an enhanced job exposure matrix, with a lag period of 10 years. We examined associations with FL risk using logistic regression accounting for relatedness between cases and controls. We performed sensitivity analyses including by control type, by sex, complete case analyses, ELF-MF exposure percentiles in addition to quartiles, ELF-MF exposure in the maximum exposed job, a shorter lag period (1 year) and the cumulative exposure in the most recent time period (1-9 years). RESULTS: We observed no association with the average intensity, duration or lifetime cumulative exposure to occupational ELF-MF exposure in the primary or sensitivity analyses. CONCLUSIONS: Our findings do not support an association between occupational ELF-MF exposure and FL risk. Although the inclusion of family members as part of the larger control group may have biased our risk estimates towards the null, findings were similar in sensitivity analyses restricted to cases and unrelated controls. Further research incorporating enhanced exposure assessment to ELF-MF is warranted to inform occupational safety regulations and any potential role in lymphomagenesis.

Inter-hospital variation in data collection, radiotherapy treatment, and survival in patients with head and neck cancer: A multisite study.

BACKGROUND AND PURPOSE: Inter-hospital inequalities in head and neck cancer (HNC) survival may exist due to variation in radiotherapy treatment-related factors. This study investigated inter-hospital variation in data collection, primary radiotherapy treatment, and survival in HNC patients from an Australian setting. MATERIALS AND METHODS: Data collected in oncology information systems (OIS) from seven Australian hospitals was extracted for 3,182 adults treated with curative radiotherapy, with or without surgery or chemotherapy, for primary, non-metastatic squamous cell carcinoma of the head and neck (2000-2017). Death data was sourced from the National Death Index using record linkage. Multivariable Cox regression was used to assess the association between survival and hospital. RESULTS: Inter-hospital variation in data collection, primary radiotherapy dose, and five-year HNC-related death was detected. Completion of eleven fields ranged from 66%-98%. Primary radiotherapy treated Tis-T1N0 glottic and any stage oral cavity and oropharynx cancers received significantly different time-corrected biologically equivalent dose in two gray fractions (EQD2T) by hospital, with observed deviation from Australian radiotherapy guidelines. Increased EQD2T dose was associated with a reduced risk of five-year HNC-related death in all patients and those treated with primary radiotherapy. Hospital, tumour site, and T and N classification were also identified as independent prognostic factors for five-year HNC-related death in all patients treated with radiotherapy. CONCLUSION: Unexplained variation exists in HNC-related death in patients treated at Australian hospitals. Available routinely collected data in OIS are insufficient to explain variation in survival. Innovative data collection, extraction, and classification practices are needed to inform clinical practice.

Prevalence of Australians exposed to potentially cardiotoxic cancer medicines: a population-based cohort study.

Background: Cardiovascular disease (CVD) and cancer are leading causes of death and people with cancer are at higher risk of developing CVD than the general population. Many cancer medicines have cardiotoxic effects but the size of the population exposed to these potentially cardiotoxic medicines is not known. We aimed to determine the prevalence of exposure to potentially cardiotoxic cancer medicines in Australia. Methods: We identified potentially cardiotoxic systemic cancer medicines through searching the literature and registered product information documents. We conducted a retrospective cohort study of Australians dispensed potentially cardiotoxic cancer medicines between 2005 and 2021, calculating age-standardised annual prevalence rates of people alive with exposure to a potentially cardiotoxic medicine during or prior to each year of the study period. Findings: We identified 108,175 people dispensed at least one potentially cardiotoxic cancer medicine; median age, 64 (IQR: 52-74); 57% female. Overall prevalence increased from 49 (95%CI: 48.7-49.3)/10,000 to 232 (95%CI: 231.4-232.6)/10,000 over the study period; 61 (95%CI: 60.5-61.5)/10,000 to 293 (95%CI: 292.1-293.9)/10,000 for females; and 39 (95%CI: 38.6-39.4)/10,000 to 169 (95%CI: 168.3-169.7)/10,000 for males. People alive five years following first exposure increased from 29 (95%CI: 28.8-29.2)/10,000 to 134 (95%CI: 133.6-134.4)/10,000; and from 22 (95%CI: 21.8-22.2)/10,000 to 76 (95%CI: 75.7-76.3)/10,000 for those alive at least 10 years following first exposure. Most people were exposed to only one potentially cardiotoxic medicine, rates of which increased from 39 (95%CI: 38.7-39.3)/10,000 in 2005 to 131 (95%CI: 130.6-131.4)/10,000 in 2021. Interpretation: The number of people exposed to efficacious yet potentially cardiotoxic cancer medicines in Australia is growing. Our findings can support the development of service planning and create awareness about the magnitude of cancer treatment-related cardiotoxicities. Funding: NHMRC Centre for Research Excellence in Medicines Intelligence, Cancer Institute NSW Early Career Fellowship.

Second Primary Cancers in People With HIV/AIDS: A National Data Linkage Study of Incidence and Risk Factors.

BACKGROUND: Evidence regarding the characteristics of second primary cancer (SPC) in people living with HIV (PLWHIV) is limited. SETTING: We performed a national population-based data linkage study to determine the incidence and risk factors of SPC in PLWHIV in Australia between 1982 and 2012. METHODS: We conducted a probabilistic data linkage study to compare the incidence of SPC over time, defined using HIV treatment eras, for SPCs related to oncogenic viral infection in comparison with non-infection-related SPCs. Risk factors considered included age at diagnosis of cancer, sex, HIV exposure modality, and CD4 + count. RESULTS: Of 29,383 individuals diagnosed with HIV, 3123 individuals who developed a first primary cancer were included in the analysis. Among them, 229 cases of SPC were identified across 27,398 person-years of follow-up. The most common SPCs were non-Hodgkin lymphomas (n = 71, 31%). The incidence of SPC overall did not change over time; however, there was an increase in individuals diagnosed with HIV in later eras ( P trend =0.001). The incidence of non-infection-related SPC increased over time and was associated with older age ( P trend = 0.005) and the acquisition of HIV in later eras ( P trend <0.001). Conversely, the incidence of infection-related SPC decreased ( P trend <0.001), but this was no longer significant after adjustment for age ( P trend = 0.14). CONCLUSIONS: The risk of SPC in PLWHIV in Australia remains high, with a temporal increase observed in non-infection-related cancer, likely due to aging of the population. Optimal screening and prevention strategies for SPC in PLWHIV are increasingly important.

The Utility of Oncology Information Systems for Prognostic Modelling in Head and Neck Cancer.

Cancer centres rely on electronic information in oncology information systems (OIS) to guide patient care. We investigated the completeness and accuracy of routinely collected head and neck cancer (HNC) data sourced from an OIS for suitability in prognostic modelling and other research. Three hundred and fifty-three adults diagnosed from 2000 to 2017 with head and neck squamous cell carcinoma, treated with radiotherapy, were eligible. Thirteen clinically relevant variables in HNC prognosis were extracted from a single-centre OIS and compared to that compiled separately in a research dataset. These two datasets were compared for agreement using Cohen's kappa coefficient for categorical variables, and intraclass correlation coefficients for continuous variables. Research data was 96% complete compared to 84% for OIS data. Agreement was perfect for gender (κ = 1.000), high for age (κ = 0.993), site (κ = 0.992), T (κ = 0.851) and N (κ = 0.812) stage, radiotherapy dose (κ = 0.889), fractions (κ = 0.856), and duration (κ = 0.818), and chemotherapy treatment (κ = 0.871), substantial for overall stage (κ = 0.791) and vital status (κ = 0.689), moderate for grade (κ = 0.547), and poor for performance status (κ = 0.110). Thirty-one other variables were poorly captured and could not be statistically compared. Documentation of clinical information within the OIS for HNC patients is routine practice; however, OIS data was less correct and complete than data collected for research purposes. Substandard collection of routine data may hinder advancements in patient care. Improved data entry, integration with clinical activities and workflows, system usability, data dictionaries, and training are necessary for OIS data to generate robust research. Data mining from clinical documents may supplement structured data collection.

Machine Learning and Nomogram Prognostic Modeling for 2-Year Head and Neck Cancer-Specific Survival Using Electronic Health Record Data: A Multisite Study.

PURPOSE: There is limited knowledge of the prediction of 2-year cancer-specific survival (CSS) in the head and neck cancer (HNC) population. The aim of this study is to develop and validate machine learning models and a nomogram for the prediction of 2-year CSS in patients with HNC using real-world data collected by major teaching and tertiary referral hospitals in New South Wales (NSW), Australia. MATERIALS AND METHODS: Data collected in oncology information systems at multiple NSW Cancer Centres were extracted for 2,953 eligible adults diagnosed between 2000 and 2017 with squamous cell carcinoma of the head and neck. Death data were sourced from the National Death Index using record linkage. Machine learning and Cox regression/nomogram models were developed and internally validated in Python and R, respectively. RESULTS: Machine learning models demonstrated highest performance (C-index) in the larynx and nasopharynx cohorts (0.82), followed by the oropharynx (0.79) and the hypopharynx and oral cavity cohorts (0.73). In the whole HNC population, C-indexes of 0.79 and 0.70 and Brier scores of 0.10 and 0.27 were reported for the machine learning and nomogram model, respectively. Cox regression analysis identified age, T and N classification, and time-corrected biologic equivalent dose in two gray fractions as independent prognostic factors for 2-year CSS. N classification was the most important feature used for prediction in the machine learning model followed by age. CONCLUSION: Machine learning and nomogram analysis predicted 2-year CSS with high performance using routinely collected and complete clinical information extracted from oncology information systems. These models function as visual decision-making tools to guide radiotherapy treatment decisions and provide insight into the prediction of survival outcomes in patients with HNC.

The future burden of oesophageal and stomach cancers attributable to modifiable behaviours in Australia: a pooled cohort study.

BACKGROUND: We quantified the individual and joint contribution of contemporaneous causal behavioural exposures on the future burden of oesophageal and stomach cancers and their subtypes and assessed whether these burdens differ between population groups in Australia, as such estimates are currently lacking. METHODS: We combined hazard ratios from seven pooled Australian cohorts (N = 367,058) linked to national cancer and death registries with exposure prevalence from the 2017-2018 National Health Survey to estimate Population Attributable Fractions (PAFs) with 95% confidence intervals (CIs), accounting for competing risk of death. RESULTS: Current and past smoking explain 35.2% (95% CI = 11.7-52.4%), current alcohol consumption exceeding three drinks/day 15.7% (95% CI = 0.9-28.4%), and these exposures jointly 41.4% (95% CI = 19.8-57.3%) of oesophageal squamous cell carcinomas in Australia. Current and past smoking contribute 38.2% (95% CI = 9.4-57.9%), obesity 27.0% (95% CI = 0.6-46.4%), and these exposures jointly 54.4% (95% CI = 25.3-72.1%) of oesophageal adenocarcinomas. Overweight and obesity explain 36.1% (95% CI = 9.1-55.1%), current and past smoking 24.2% (95% CI = 4.2-40.0%), and these exposures jointly 51.2% (95% CI = 26.3-67.8%) of stomach cardia cancers. Several population groups had a significantly higher smoking-attributable oesophageal cancer burden, including men and those consuming excessive alcohol. CONCLUSIONS: Smoking is the leading preventable behavioural cause of oesophageal cancers and overweight/obesity of stomach cancers.

Australian genome-wide association study confirms higher female risk for adult glioma associated with variants in the region of CCDC26.

BACKGROUND: Glioma accounts for approximately 80% of malignant adult brain cancer and its most common subtype, glioblastoma, has one of the lowest 5-year cancer survivals. Fifty risk-associated variants within 34 glioma genetic risk regions have been found by genome-wide association studies (GWAS) with a sex difference reported for 8q24.21 region. We conducted an Australian GWAS by glioma subtype and sex. METHODS: We analyzed genome-wide data from the Australian Genomics and Clinical Outcomes of Glioma (AGOG) consortium for 7 573 692 single nucleotide polymorphisms (SNPs) for 560 glioma cases and 2237 controls of European ancestry. Cases were classified as glioblastoma, non-glioblastoma, astrocytoma or oligodendroglioma. Logistic regression analysis was used to assess the associations of SNPs with glioma risk by subtype and by sex. RESULTS: We replicated the previously reported glioma risk associations in the regions of 2q33.3 C2orf80, 2q37.3 D2HGDH, 5p15.33 TERT, 7p11.2 EGFR, 8q24.21 CCDC26, 9p21.3 CDKN2BAS, 11q21 MAML2, 11q23.3 PHLDB1, 15q24.2 ETFA, 16p13.3 RHBDF1, 16p13.3 LMF1, 17p13.1 TP53, 20q13.33 RTEL, and 20q13.33 GMEB2 (P < .05). We also replicated the previously reported sex difference at 8q24.21 CCDC26 (P = .0024) with the association being nominally significant for both sexes (P < .05). CONCLUSIONS: Our study supports a stronger female risk association for the region 8q24.21 CCDC26 and highlights the importance of analyzing glioma GWAS by sex. A better understanding of sex differences could provide biological insight into the cause of glioma with implications for prevention, risk prediction and treatment.