RESUMO
IMPORTANCE: Residual cancer burden (RCB) distributions may improve the interpretation of efficacy in neoadjuvant breast cancer trials. OBJECTIVE: To compare RCB distributions between randomized control and investigational treatments within subtypes of breast cancer and explore the relationship with survival. DESIGN, SETTING, AND PARTICIPANTS: The I-SPY2 is a multicenter, platform adaptive, randomized clinical trial in the US that compares, by subtype, investigational agents in combination with chemotherapy vs chemotherapy alone in adult women with stage 2/3 breast cancer at high risk of early recurrence. Investigational treatments graduated in a prespecified subtype if there was 85% or greater predicted probability of higher rate of pathologic complete response (pCR) in a confirmatory, 300-patient, 1:1 randomized, neoadjuvant trial in that subtype. Evaluation of a secondary end point was reported from the 10 investigational agents tested in the I-SPY2 trial from March 200 through 2016, and analyzed as of September 9, 2020. The analysis plan included modeling of RCB within subtypes defined by hormone receptor (HR) and ERBB2 status and compared control treatments with investigational treatments that graduated and those that did not graduate. INTERVENTIONS: Neoadjuvant paclitaxel plus/minus 1 of several investigational agents for 12 weeks, then 12 weeks of cyclophosphamide/doxorubicin chemotherapy followed by surgery. MAIN OUTCOMES AND MEASURES: Residual cancer burden (pathological measure of residual disease) and event-free survival (EFS). RESULTS: A total of 938 women (mean [SD] age, 49 [11] years; 66 [7%] Asian, 103 [11%] Black, and 750 [80%] White individuals) from the first 10 investigational agents were included, with a median follow-up of 52 months (IQR, 29 months). Event-free survival worsened significantly per unit of RCB in every subtype of breast cancer (HR-positive/ERBB2-negative: hazard ratio [HZR], 1.75; 95% CI, 1.45-2.16; HR-positive/ERBB2-positive: HZR, 1.55; 95% CI, 1.18-2.05; HR-negative/ERBB2-positive: HZR, 2.39; 95% CI, 1.64-3.49; HR-negative/ERBB2-negative: HZR, 1.99; 95% CI, 1.71-2.31). Prognostic information from RCB was similar from treatments that graduated (HZR, 2.00; 95% CI, 1.57-2.55; 254 [27%]), did not graduate (HZR, 1.87; 95% CI, 1.61-2.17; 486 [52%]), or were control (HZR, 1.79; 95% CI, 1.42-2.26; 198 [21%]). Investigational treatments significantly lowered RCB in HR-negative/ERBB2-negative (graduated and nongraduated treatments) and ERBB2-positive subtypes (graduated treatments), with improved EFS (HZR, 0.61; 95% CI, 0.41-0.93) in the exploratory analysis. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, the prognostic significance of RCB was consistent regardless of subtype and treatment. Effective neoadjuvant treatments shifted the distribution of RCB in addition to increasing pCR rate and appeared to improve EFS. Using a standardized quantitative method to measure response advances the interpretation of efficacy. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01042379.
Assuntos
Neoplasias da Mama , Terapia Neoadjuvante , Adulto , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Neoplasias da Mama/patologia , Feminino , Humanos , Pessoa de Meia-Idade , Terapia Neoadjuvante/métodos , Neoplasia Residual , Prognóstico , Intervalo Livre de Progressão , Receptor ErbB-2/análiseRESUMO
OBJECTIVE: The objective of this study was to study provider attitudes of and perceived barriers to the clinical use of pharmacogenomics before and during participation in an implementation program. PARTICIPANTS AND METHODS: From 2012 to 2017, providers were recruited. After completing semistructured interviews (SSIs) about pharmacogenomics, providers received training on and access to a clinical decision support tool housing patient-specific pharmacogenomic results. Thematic analysis of SSI was conducted (inter-rater reliability κ≥0.75). Providers also completed surveys before and during study participation, and provider-perceived barriers to pharmacogenomic implementation were analyzed. RESULTS: Seven themes emerged from the SSI (listed from most frequent to least): decision-making, concerns with pharmacogenomic adoption, outcome expectancy, provider knowledge of pharmacogenomics, patient attitudes, individualized treatment, and provider interest in pharmacogenomics. Although there was prestudy enthusiasm among all providers, concerns with clinical utility, time, results accession, and knowledge of pharmacogenomics were frequently stated at baseline. Despite this, adoption of pharmacogenomics was robust, as patient-specific results were accessed at 64% of visits, and medication changes were influenced by provided pharmacogenomic information 42% of the time. Providers reported they had enough time to evaluate the information and the results were easily understood on 74 and 98% of surveys, respectively. Nevertheless, providers consistently felt there was insufficient pharmacogenomic information for most drugs they prescribed and clear guidelines for using pharmacogenomic information were lacking. CONCLUSION: Despite initial concerns about adequate time and knowledge for adoption, providers frequently utilized pharmacogenomic results. Provider-perceived barriers to wider use included lack of clear guidelines and evidence for most drugs, highlighting important considerations for the field of pharmacogenomics.