Standardizing Breast Adjuvant Radiation Therapy Practices in a Diverse Health System through Development of a Delphi Consensus Supported Clinical Algorithm.
Int J Radiat Oncol Biol Phys 2023;
117:e210. [PMID:
37784876 DOI:
10.1016/j.ijrobp.2023.06.1098]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S)
Adjuvant radiation therapy (RT) for early breast cancer is a highly effective treatment option. However, the multitude of available techniques backed by strong clinical evidence can result in a lack of consistency in treatment approaches, even within a single healthcare organization. This presents challenges for both providers and patients in making informed decisions. To address this issue, our radiation department, which serves a large and diverse health system, developed a clinical algorithm for adjuvant RT for breast cancer. This algorithm was created to enhance the quality and standardization of care delivered across our network.
MATERIALS/METHODS
A modified Delphi technique was used. A panel of eight experienced breast radiation oncologists from our institution was assembled. The panel first identified the common clinical scenarios encountered in treating patients with adjuvant breast RT, and then made recommendations for the primary and alternative approaches for each scenario. NCCN guidelines, ASTRO executive summaries, and published national and international randomized trials were used for reference. In case of disagreements, the final recommendation was reached through a majority vote. The draft algorithm was also shared with medical oncologists, surgeons, and patient advocates to gather their input prior to final approval by the expert panel.
RESULTS
Consensus was reached for three broad clinical scenarios for patients who have undergone lumpectomy or mastectomy: Ductal Carcinoma in Situ (DCIS), Invasive Cancer Node Negative (ICN0), and Invasive Cancer Node Positive (ICN+). The panel agreed subdivision of the scenarios into three risk groups (low, intermediate, and high) and three age groups, based on guidelines and consensus statements. For DCIS patients, size, grade, margin status, hormone receptor status, and tumor focality were used for further stratification. For ICN0 patients, HER2 receptor status and lymphovascular space invasion were also included. For ICN+ patients, nodal status (negative versus 1-3 positive nodes versus more than 3 positive nodes) was used for stratification. Additionally, DCIS and ICN0 patients were further divided into age groups. The panel reached consensus recommendations for RT, including whole breast RT, partial breast RT, chest wall RT, regional nodal irradiation, or omission of RT for each sub-group. Clinical trial enrollment was also recommended where appropriate.
CONCLUSION
A breast cancer adjuvant RT algorithm was developed with the aim of standardizing care for patients with breast cancer. Implementation is expected to standardize treatment recommendations in our health system and to streamline the shared decision-making process with patients.
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