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Stephane Heritier

Publications and source records attributed to Stephane Heritier.

2 recordsLinked to original sources

Psychosocial factors and patients' preferences for adjuvant chemotherapy in early breast cancer.

PURPOSE: Many women who have had adjuvant chemotherapy for early breast cancer judge small benefits sufficient to make it worthwhile despite significant side effects and inconvenience. The rationality of these preferences has been questioned. We sought to better understand such preferences by assessing associations between preferences and psychosocial factors, and by asking women who judged negligible benefits sufficient to explain why. METHODS: We recruited 83 consecutive consenting women who had completed adjuvant chemotherapy for early breast cancer 3-34 months earlier. Preferences were elicited during a structured, scripted interview using four sets of validated, hypothetical trade-off scenarios about the possible benefits of adjuvant chemotherapy on survival times (5 and 15 years) and rates (65 and 85% at 5 years). Women completed questionnaires measuring anxiety, depression, optimism, quality and quantity of social support, and illness perceptions. RESULTS: More than half the women judged benefits of 1 day or 0.1% sufficient to make adjuvant chemotherapy worthwhile. The most important factors in multivariable models were whether the woman had dependants and number of non-specific symptoms attributed to breast cancer and adjuvant chemotherapy since completing treatment. The proportion of variance explained was modest. Preferences were not associated with: scores for anxiety, optimism, and perceived quality and quantity of social support. Explanations for judging negligible benefits sufficient included minimising regret, parenting concerns, doubts about the information provided and feeling that they had no choice. CONCLUSIONS: Preferences were highly variable and influenced by women's unique circumstances and attitudes, but not by their anxiety or optimism scores.

Adult↗

Dynamic balancing randomization in controlled clinical trials.

In the design of randomized clinical trials, balancing of treatment allocation across important prognostic factors (strata) improves the efficiency of the final comparisons. Whilst randomization methods exist which attempt to balance treatments across the strata (permuted blocks, minimization, biased coin), these approaches assign equal importance for all the strata. Dynamic balancing randomization (DBR) is a tree-based method proposed by Signorini et al. allowing different levels of imbalance in different strata which ensures a balance for each level of prognostic risk factors (conditional balance) whilst at the same time preserving randomness. We present a simple modification to the original approach to maintain a marginal balance over important strata and examine the properties of this modification. Two important measures of performance are used to provide comparisons between the approaches: a loss function, which can be interpreted as the squared norm of the imbalance vector, and a forcing index which conveys the degree of randomness. A comparison of DBR with minimization and a biased coin design is carried out by simulation on two simulated trials.

Humans↗