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Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers.

ABSTRACT: BACKGROUND:Most risk models for cancer are either specific to individual cancers or include complex or predominantly non-modifiable risk factors. METHODS:We developed lifestyle-based models for the five cancers for which the most cases are potentially preventable through lifestyle change in the UK (lung, colorectal, bladder, kidney, and esophageal for men and breast, lung, colorectal, endometrial, and kidney for women). We selected lifestyle risk factors from the European Code against Cancer and obtained estimates of relative risks from meta-analyses of observational studies. We used mean values for risk factors from nationally representative samples and mean 10-year estimated absolute risks from routinely available sources. We then assessed the performance of the models in 23,768 participants in the EPIC-Norfolk cohort who had no history of the five selected cancers at baseline. RESULTS:In men, the combined risk model showed good discrimination [AUC, 0.71; 95% confidence interval (CI), 0.69-0.73] and calibration. Discrimination was lower in women (AUC, 0.59; 95% CI, 0.57-0.61), but calibration was good. In both sexes, the individual models for lung cancer had the highest AUCs (0.83; 95% CI, 0.80-0.85 for men and 0.82; 95% CI, 0.76-0.87 for women). The lowest AUCs were for breast cancer in women and kidney cancer in men. CONCLUSIONS:The discrimination and calibration of the models are both reasonable, with the discrimination for individual cancers comparable or better than many other published risk models. IMPACT:These models could be used to demonstrate the potential impact of lifestyle change on risk of cancer to promote behavior change.

SUBMITTER: Usher-Smith JA

PROVIDER: S-EPMC6330056 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers.

Usher-Smith Juliet A JA Sharp Stephen J SJ Luben Robert R Griffin Simon J SJ

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20180913 1

<h4>Background</h4>Most risk models for cancer are either specific to individual cancers or include complex or predominantly non-modifiable risk factors.<h4>Methods</h4>We developed lifestyle-based models for the five cancers for which the most cases are potentially preventable through lifestyle change in the UK (lung, colorectal, bladder, kidney, and esophageal for men and breast, lung, colorectal, endometrial, and kidney for women). We selected lifestyle risk factors from the European Code aga ...[more]

PMID: 30213791

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Project description:Background and study aims Previous research has shown that providing cancer risk information to people can improve their understanding of their risk of cancer, increase their intention to attend cancer screening, and increase their fruit and vegetable intake and physical activity. A risk calculator has been developed and tested based on modifiable behavioural risk factors, such as weight and smoking, which estimates the risk of an individual developing one of the five most common preventable cancers in the UK over a 10-year period. These cancers are lung, bowel, bladder, kidney and oesophageal cancer for men and breast, lung, bowel, endometrial and kidney cancer for women). Alongside 66 healthcare professionals who have taken part in focus groups and interviews, a web-based tool has been developed which allows people to enter details of their current lifestyle and then see their estimated risk of developing one of the cancers over the next 10 years, the effect changes in their lifestyle would make on that risk, and lifestyle advice. The aim of this study is to use that web-based tool to test whether people given their personalised cancer risk estimate in combination with lifestyle advice are more motivated to make changes in their behaviour than people given lifestyle advice alone. The study also compares different ways of presenting the risk information. Who can participate? Men and women aged 30-74 who do not have a past history of cancer What does the study involve? Participants answer a set of questions about their diet, lifestyle and beliefs about their risk of cancer. They are then randomly allocated to be presented with their personalised 10-year cancer risk and lifestyle advice, or go straight to the lifestyle advice without seeing their personalised risk. The cancer risk is presented in one of three formats. The first format is a bar chart, the second format is pictures of either 1000 or 100 faces depending on the individual's estimated risk, and the third format is a bar with a scale from below average to above average with arrows. Participants then answer a further set of questions about their thoughts about their risk of cancer and motivation to make lifestyle change. They are then asked if they agree to take part in a follow-up task 3 months later where they answer a similar set of questions to check how their lifestyle and ideas about cancer risk have changed with time. After completing that task, if they are one of the people who did not see their personalised risk in the first task, they are offered the opportunity to see it then.

Project description:Indicators of potentially preventable hospitalisations have been adopted internationally as a measure of health system performance; however, few assess appropriate processes of care around medication use, that if followed may prevent hospitalisation. The aim of this study was to develop and validate evidence-based medication-related indicators of potentially preventable hospitalisations.Australian primary healthcare.Medical specialists, general practitioners and pharmacists. A modified RAND appropriateness method was used for the development of medication-related indicators of potentially preventable hospitalisations, which included a literature review, assessment of the strength of the supporting evidence base, an initial face and content validity by an expert panel, followed by an independent assessment of indicators by an expert clinical panel across various disciplines, using an online survey.Analysis of ratings was performed on the four key elements of preventability; the medication-related problem must be recognisable, the adverse outcomes foreseeable and the causes and outcomes identifiable and controllable.A total of 48 potential indicators across all major disease groupings were developed based on level III evidence or greater, that were independently assessed by 78 expert clinicians (22.1% response rate). The expert panel considered 29 of these (60.4%) sufficiently valid. Of these, 21 (72.4%) were based on level I evidence.This study provides a set of face and content validated indicators of medication-related potentially preventable hospitalisations, linking suboptimal processes of care and medication use with subsequent hospitalisation. Further analysis is required to establish operational validity in a population-based sample, using an administrative health database. Implementation of these indicators within routine monitoring of healthcare systems will highlight those conditions where hospitalisations could potentially be avoided through improved medication management.

Project description:IntroductionThe proportion of potentially preventable hospitalisations (PPH) which are actually preventable is unknown, and little is understood about the factors associated with individual preventable PPH. The Diagnosing Potentially Preventable Hospitalisations (DaPPHne) Study aimed to determine the proportion of PPH for chronic conditions which are preventable and identify factors associated with chronic PPH classified as preventable.SettingThree hospitals in NSW, Australia.ParticipantsCommunity-dwelling patients with unplanned hospital admissions between November 2014 and June 2017 for congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), diabetes complications or angina pectoris. Data were collected from patients, their general practitioners (GPs) and hospital records.Outcome measuresAssessments of the preventability of each admission by an Expert Panel.Results323 admissions were assessed for preventability: 46% (148/323) were assessed as preventable, 30% (98/323) as not preventable and 24% (77/323) as unclassifiable. Statistically significant differences in proportions preventable were found between the three study sites (29%; 47%; 58%; p≤0.001) and by primary discharge diagnosis (p≤0.001).Significant predictors of an admission being classified as preventable were: study site; final principal diagnosis of CHF; fewer diagnoses on discharge; shorter hospital stay; GP diagnosis of COPD; GP consultation in the last 12 months; not having had a doctor help make the decision to go to hospital; not arriving by ambulance; patient living alone; having someone help with medications and requiring help with daily tasks.ConclusionsThat less than half the chronic PPH were assessed as preventable, and the range of factors associated with preventability, including site and discharge diagnosis, are important considerations in the validity of PPH as an indicator. Opportunities for interventions to reduce chronic PPH include targeting patients with CHF and COPD, and the provision of social welfare and support services for patients living alone and those requiring help with daily tasks and medication management.

Dataset Information

Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers.

Publications

Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers.

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