Effects of Radiotherapy in Early-Stage, Low-Recurrence Risk, Hormone-Sensitive Breast Cancer

Jinani Jayasekera; Clyde B. Schechter; Joseph A. Sparano, Reshma Jagsi; Julia White; Judith-Anne W. Chapman; Timothy Whelan; Stewart J. Anderson; Anthony W. Fyles; Willi Sauerbrei; Richard C. Zellars; Yisheng Li; Juhee Song; Xuelin Huang; Thomas B. Julian; George Luta; Donald A. Berry; Eric J. Feuer; Jeanne Mandelblatt; for the CISNET-BOLD Collaborative Group

Disclosures

J Natl Cancer Inst. 2018;110(12):1370-1379. 

In This Article

Methods

Data Sources

Members of the Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Working Group conducted this study in collaboration with the National Cancer Institute (NCI) Breast Cancer Steering Committee's Breast Oncology Local Disease (BOLD) Task Force, and clinical trial investigators from the seven clinical trials. The study was considered exempt by the Georgetown University Oncology Institutional Review Board because it used de-identified secondary data released for research purposes under NCI data-sharing policies.

Study Design and Population

We adapted the inclusion criteria from a recent clinical trial proposed by NRG Oncology to evaluate omission of radiotherapy after breast conservation among patients aged 40–74 years with low-risk breast cancers with planned hormonal therapy and no chemotherapy. "Low-risk" cancers were defined as AJCC (version 6) primary invasive stage I disease (≤2 cm pathological tumor size, pathologically/clinically node-negative),[12] estrogen receptor (ER)-positive and/or progesterone receptor (PR)-positive, and human epidermal growth factor-2 (HER2) negative or unknown. An additional eligibility criterion was Oncotype DX score of no more than 18 (Figure 1).

Figure 1.

Selection of patients with stage I, lymph node–negative, ER and/or PR+, HER2− breast cancer with Oncotype DX score ≤ 18, treated with breast conservation and hormonal therapy. *Randomly assigned to radiotherapy N = 304, Radiotherapy given per treatment protocol N = 1101; †Randomly assigned to no radiotherapy N = 312, Radiotherapy not given per treatment protocol N = 61. Assumed 100% compliance to protocol. ER = estrogen receptor; PR = progesterone receptor; HER2− = human epidermal growth factor-2 negative.

Data Collection

Seventeen trials were included in the 2011 Oxford meta-analysis of the effects of radiotherapy.[2] Of these, we considered the seven trials categorized as "evaluating the need for radiotherapy after lumpectomy in low-risk patients".[3,6–11,13–15] Detailed information about the trials is included in Supplementary Table 1 (available online).

Study Endpoints

The primary endpoint was recurrence-free interval (RFI),[16,17] and included time from random assignment/enrollment to any occurrence of local (invasive), regional, or distant recurrence, or breast cancer death. This endpoint was censored at the time of contralateral breast cancer, other second primary cancers, or other-cause death.

Secondary endpoints were RFI by type of recurrence (locoregional or distant), overall survival (time from random assignment/enrollment to death), and breast cancer–specific survival (time from random assignment/enrollment to breast cancer death). The patients were followed up to 10 years because many trials did not follow patients for recurrence beyond this period. Published TAILORx data were truncated at five years,[8] so we utilized the same length of follow-up for that trial.

Intervention and Covariates

Radiotherapy (yes/no) was the intervention of interest. Other factors examined as potential covariates or subgroups were patient age, tumor grade (low/moderate/high/unknown), ER and PR status (ER+ and PR+/other), HER2 (negative/unknown), initial hormonal treatment (tamoxifen/aromatase inhibitors/other), tumor size (<1 cm/>1 cm), trial, and Oncotype DX score.

Statistical Analysis

The primary analysis was conducted by combining data from the trials into a summary effect for radiotherapy without weighting.[18,19] Prior to pooling the data, the study-specific effects of radiotherapy were estimated, and homogeneity was examined using the Cochran Q test. Because the trials were not homogeneous in effect, trial was included as a covariate in subsequent analyses.

The TAILORx trial included Oncotype data and was published after the 2011 Oxford overview.[2,8] Therefore, except for patients in the TAILORx study, Oncotype scores (0–100) were imputed for the other six trials using a deterministic regression–based multiple imputation approach[20] and a population-based donor dataset with Oncotype scores (Supplementary Methods, available online).[21,22] The imputation model included age, tumor size, grade, radiation, and ER/PR and HER2 status. Coefficients and standard errors from all analyses were adjusted for variability between imputations according to the combination rules outlined by Rubin (1987).[20]

We examined the distribution of patient characteristics overall, by radiotherapy and study. After individual data were pooled and study-eligible patients selected, the women in the final analytic sample were no longer randomly assigned to radiotherapy. This resulted in an imbalance in baseline characteristics between the no-RT vs RT groups. Therefore, multivariable Cox proportional hazards models were used to examine study endpoints and derive survival plots by radiotherapy, adjusting for other covariates. The primary test statistic for multiple imputation estimates was a Student t test with the degrees of freedom depending on the number of imputations and the increase in variance of estimates due to missing data; the results were considered statistically significant if the two-sided P value was less than .05. All models consistently supported the assumption of proportional hazards and Cox–Snell residuals indicated good model fit. Analyses were repeated to determine the effects of radiotherapy on secondary outcomes. The adjusted five- and 10-year RFI and breast cancer–specific and all-cause survival rates were calculated using adjusted Cox proportional hazards models. All statistical tests were two-sided.

Subgroup Analyses

Exploratory analyses were conducted to evaluate the effects of radiotherapy within subgroups based on age at random assignment/enrollment (<60/60–70/70+ years), hormone receptor status (ER+ and PR+/other), Oncotype (0–10/11–18), grade (low and intermediate/high), and tumor size (≤1 cm/>1 cm).

Sensitivity Analyses

We evaluated RFI, locoregional RFI, and distant RFI using competing risk models to estimate subdistribution hazard ratios and 95% confidence intervals considering other-cause mortality as a competing event using the methods described by Gray.[23] In competing risk analyses, differences in endpoints were adjusted for potential risk factors with statistical significance determined using a two-sided Wald test.

We also performed a propensity score analysis of radiotherapy effect on RFI and type of RFI. A logistic regression model estimated the propensity to receive radiotherapy, given patient characteristics and study and interaction terms (Supplementary Methods, available online). The results were then used to calculate inverse-probability-of-treatment-weighted estimates in Cox models.

We examined the effects of radiotherapy on endpoints excluding women from NSABP B-14, B-20, and TAILORx trials, the three trials where receipt of radiotherapy was not randomized. A second sensitivity analysis examined the effect of including older women (74 years and older). Adjusted RFI hazard ratios (HRs) were also estimated with data truncated at five and nine years.

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