Prospective, multicenter French study evaluating the clinical impact of the Breast Cancer Intrinsic Subtype-Prosigna® Test in the management of early-stage breast cancers

Purpose The Prosigna® breast cancer prognostic gene signature assay identifies a gene-expression profile that permits the classification of tumors into subtypes and gives a score for the risk of recurrence (ROR) at 10 years. The primary objective of this multicenter study was to evaluate the impact of Prosigna’s assay information on physicians’ adjuvant treatment decisions in patients with early-stage breast cancer. Secondary objectives were to assess confidence of practitioners in their therapeutic recommendations before and after the added information provided by the Prosigna assay; and to evaluate the emotional state of patients before and after the Prosigna test results. Methods Consecutive patients with invasive early-stage breast cancer were enrolled in a prospective, observational, multicenter study carried out in 8 hospitals in France. The Prosigna test was carried out on surgical specimens using the nCounter® Analysis System located at the Institut Curie. Both before and after receiving the Prosigna test results, physicians completed treatment confidence questionnaires and patients completed questionnaires concerning their state of anxiety, the difficulties felt in face of the therapy and quality of life. Information was also collected at 6 months regarding the physicians’ opinion on the test results and the patients’ degree of anxiety, difficulties with therapy and quality of life. Results Between March 2015 and January 2016, 8 study centers in France consecutively enrolled 210 postmenopausal women with estrogen receptor (ER) positive, human epidermal growth hormone-2 (HER-2) negative, and node negative tumors, either stage 1 or stage 2. Intrinsic tumor subtypes as assessed by the Prosigna test were 114 (58.2%) Luminal A, 79 (40.3%) Luminal B, 1 (0.5%) HER-2 enriched (HER-2E), and 2 (1.0%) basal-like. Before receiving the Prosigna test results, physicians categorized tumor subtypes based on immunohistochemistry (IHC) as Luminal A in 126 (64%) patients and Luminal B in 70 (36%) patients, an overall discordance rate of 25%. The availability of Prosigna assay results was significantly associated with the likelihood of change in treatment recommendations, with 34 patients (18%) having their treatment plan changed from Adjuvant Chemotherapy to No Adjuvant Chemotherapy or vice versa (p<0.001, Fisher’s exact test). Prosigna test results also decreased patients’ anxiety about the chosen adjuvant therapy, and improved emotional well-being and measures of personal perceptions of uncertainty. Conclusions The results of this prospective decision impact study are consistent with 2 previous, identically designed studies carried out in Spain and Germany. The availability of Prosigna test results increased the confidence of treating physicians in their adjuvant treatment decisions, and led to an 18% change in chemotherapy treatment plan (from Adjuvant Chemotherapy to No Adjuvant Chemotherapy or vice versa). Prosigna testing decreased anxiety and improved measures of health-related quality of life in patients facing adjuvant therapy. The 25% discordance between Prosigna test and IHC subtyping underlines the importance of molecular testing for optimal systemic therapy indications in early breast cancer.


Introduction
Background 2 Scientific background and explanation of rationale Theories used in designing behavioral interventions

Methods
Participants 3 Eligibility criteria for participants, including criteria at different levels in recruitment/sampling plan (e.g., cities, clinics, subjects) Method of recruitment (e.g., referral, self-selection), including the sampling method if a systematic sampling plan was implemented Recruitment setting Settings and locations where the data were collected Interventions 4 Details of the interventions intended for each study condition and how and when they were actually administered, specifically including: Unit of assignment (the unit being assigned to study condition, e.g., individual, group, community) Method used to assign units to study conditions, including details of any restriction (e.g., blocking, stratification, minimization) Inclusion of aspects employed to help minimize potential bias induced due to non-randomization (e.g., matching) Whether or not participants, those administering the interventions, and those assessing the outcomes were blinded to study condition assignment; if so, statement regarding how the blinding was accomplished and how it was assessed.
Unit of Analysis 10 Description of the smallest unit that is being analyzed to assess intervention effects (e.g., individual, group, or community) If the unit of analysis differs from the unit of assignment, the analytical method used to account for this (e.g., adjusting the standard error estimates by the design effect or using multilevel analysis) Statistical Methods

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Statistical methods used to compare study groups for primary methods outcome(s), including complex methods of correlated data Statistical methods used for additional analyses, such as a subgroup analyses and adjusted analysis Methods for imputing missing data, if used Statistical software or programs used

Participant flow 12
Flow of participants through each stage of the study: enrollment, assignment, allocation, and intervention exposure, follow-up, analysis (a diagram is strongly recommended) o Enrollment: the numbers of participants screened for eligibility, found to be eligible or not eligible, declined to be enrolled, and enrolled in the study o Assignment: the numbers of participants assigned to a study condition o Allocation and intervention exposure: the number of participants assigned to each study condition and the number of participants who received each intervention o Follow-up: the number of participants who completed the followup or did not complete the follow-up (i.e., lost to follow-up), by study condition o Analysis: the number of participants included in or excluded from the main analysis, by study condition Description of protocol deviations from study as planned, along with reasons Recruitment 13 Dates defining the periods of recruitment and follow-up Baseline Data 14 Baseline demographic and clinical characteristics of participants in each study condition Baseline characteristics for each study condition relevant to specific disease prevention research Baseline comparisons of those lost to follow-up and those retained, overall and by study condition Comparison between study population at baseline and target population of interest Baseline equivalence 15 Data on study group equivalence at baseline and statistical methods used to control for baseline differences  Numbers analyzed 16 Number of participants (denominator) included in each analysis for each study condition, particularly when the denominators change for different outcomes; statement of the results in absolute numbers when feasible Indication of whether the analysis strategy was "intention to treat" or, if not, description of how non-compliers were treated in the analyses Outcomes and estimation 17 For each primary and secondary outcome, a summary of results for each estimation study condition, and the estimated effect size and a confidence interval to indicate the precision Inclusion of null and negative findings Inclusion of results from testing pre-specified causal pathways through which the intervention was intended to operate, if any Ancillary analyses 18 Summary of other analyses performed, including subgroup or restricted analyses, indicating which are pre-specified or exploratory Adverse events 19 Summary of all important adverse events or unintended effects in each study condition (including summary measures, effect size estimates, and confidence intervals)

Interpretation 20
Interpretation of the results, taking into account study hypotheses, sources of potential bias, imprecision of measures, multiplicative analyses, and other limitations or weaknesses of the study Discussion of results taking into account the mechanism by which the intervention was intended to work (causal pathways) or alternative mechanisms or explanations Discussion of the success of and barriers to implementing the intervention, fidelity of implementation Discussion of research, programmatic, or policy implications Generalizability 21 Generalizability (external validity) of the trial findings, taking into account the study population, the characteristics of the intervention, length of follow-up, incentives, compliance rates, specific sites/settings involved in the study, and other contextual issues Overall Evidence

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General interpretation of the results in the context of current evidence and current theory