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A Bayesian CUSUM plot: Diagnosing quality of treatment
Author(s) -
Rosthøj Steen,
Jacobsen RikkeLine
Publication year - 2017
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/jep.12815
Subject(s) - cusum , odds , statistics , plot (graphics) , bayesian probability , survival analysis , odds ratio , medicine , series (stratigraphy) , bayes' theorem , credible interval , confidence interval , mathematics , logistic regression , biology , paleontology
Objectives To present a CUSUM plot based on Bayesian diagnostic reasoning displaying evidence in favour of “healthy” rather than “sick” quality of treatment (QOT), and to demonstrate a technique using Kaplan‐Meier survival curves permitting application to case series with ongoing follow‐up. Methods For a case series with known final outcomes: Consider each case a diagnostic test of good versus poor QOT (expected vs. increased failure rates), determine the likelihood ratio (LR) of the observed outcome, convert LR to weight taking log to base 2, and add up weights sequentially in a plot showing how many times odds in favour of good QOT have been doubled. For a series with observed survival times and an expected survival curve: Divide the curve into time intervals, determine “healthy” and specify “sick” risks of failure in each interval, construct a “sick” survival curve, determine the LR of survival or failure at the given observation times, convert to weights, and add up. Results The Bayesian plot was applied retrospectively to 39 children with acute lymphoblastic leukaemia with completed follow‐up, using Nordic collaborative results as reference, showing equal odds between good and poor QOT. In the ongoing treatment trial, with 22 of 37 children still at risk for event, QOT has been monitored with average survival curves as reference, odds so far favoring good QOT 2:1. Conclusion QOT in small patient series can be assessed with a Bayesian CUSUM plot, retrospectively when all treatment outcomes are known, but also in ongoing series with unfinished follow‐up.