Abstract

BackgroundThe Melanoma Genomics Managing Your Risk Study is a randomised controlled trial that aims to evaluate the efficacy of providing information on personal genomic risk of melanoma in reducing ultraviolet radiation (UV) exposure, stratified by traditional risk group (low or high phenotypic risk) in the general population. The primary outcome is objectively measured total daily Standard Erythemal Doses at 12 months. Secondary outcomes include UV exposure at specific time periods, self-reported sun protection and skin-examination behaviours, psychosocial outcomes, and ethical considerations surrounding offering genomic testing at a population level. A within-trial and modelled economic evaluation will be undertaken from an Australian health system perspective to assess the cost-effectiveness of the intervention.ObjectiveTo publish the pre-determined statistical analysis plan (SAP) before database lock and the start of analysis.MethodsThis SAP describes the data synthesis, analysis principles and statistical procedures for analysing the outcomes from this trial. The SAP was approved after closure of recruitment and before completion of patient follow-up. It outlines the planned primary analyses and a range of subgroup and sensitivity analyses. Health economic outcomes are not included in this plan but will be analysed separately. The SAP will be adhered to for the final data analysis of this trial to avoid potential analysis bias that may arise from knowledge of the outcome data.ResultsThis SAP is consistent with best practice and should enable transparent reporting.ConclusionThis SAP has been developed for the Melanoma Genomics Managing Your Risk Study and will be followed to ensure high-quality standards of internal validity and to minimise analysis bias.Trial registrationProspectively registered with the Australian New Zealand Clinical Trials Registry, ID: ACTR N12617000691347. Registered on 15 May 2017.

Highlights

  • PrefaceMelanoma is a serious form of skin cancer associated with significant morbidity and mortality but is highly preventable through individual behaviour change [1, 2].Reduced sun exposure and improved primary prevention behaviours could prevent over 80%of melanoma diagnoses [3]

  • This statistical analysis plan (SAP) has been developed for the Melanoma Genomics Managing Your Risk Study and will be followed to ensure high-quality standards of internal validity and to minimise analysis bias

  • Genomic risk information, based on multiple common genetic variants associated with elevated risk, could be integrated into improved melanoma prevention and early detection strategies [5, 6]

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Summary

Methods

General study design and plan The Melanoma Genomics Managing Your Risk Study is a parallel-group, two-arm, RCT with a 1:1 allocation ratio. Missing data The number of participants who complete the 12-month follow-up will be described by allocation; the study arms will be compared using chi-square tests and logistic regression to see if the attrition rate differs by arm and to compare baseline characteristics of participants who did and did not complete follow-up Of those who complete follow-up, each variable will be examined for the presence of missing data and if > 10% is observed for primary or secondary outcomes, sensitivity analyses will be performed using complete case analysis or multiple imputation methods assuming data are missing at random (MAR). Where outcomes were assessed at two time points only (baseline and 12 months), data will be analysed using ANCOVA for continuous outcome measures [40], and using GLM with log link function for binomial outcome variables to estimate relative risks and 95% CIs. The mean difference and 95% CIs between intervention and control groups at 12 months will be estimated. The reviewing statistician will have an overview of all the analyses and will check the code, producing tables selected at random as well as any other pieces of code as desired

Conclusion
The intervention’s effect on short-term outcomes at 1 month
Availability of data and materials Not applicable
Full Text
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