Abstract PS6-10: Risk estimation of locoregional recurrence, distant metastasis and second primary breast cancer in early stage breast cancer patients: The INFLUENCE 2.0 nomogram
Authors: Siesling Sabine , Völkel Vinzenz , Hueting Tom , Draeger Teresa , van Maaren Marissa C , Strobbe Luc JA , Schmidt Marjanka K , Sonke Gabe S , van Hezewijk Marjan , Groothuis-Oudshoorn Catharina GM 
Published: February 2021

Background Breast cancer follow-up aims at early detection of locoregional recurrences (LRR) and second primary breast cancer (SP). Predicting a patient’s time-dependent risk for such an event may improve follow-up strategies. Furthermore, many clinicians and patients are interested in the risk of distant metastasis (DM) as well, as it provides additional information on prognosis. The existing INFLUENCE nomogram predicts the yearly risk of LRR up to five years from diagnosis using logistic regression analyses. However, this model was based on patients diagnosed between 2003 and 2006 and lacked information on HER2 status, which is nowadays an important prognostic variable. In this population-based study, we aimed to improve the INFLUENCE model with more flexible predictions over time, more recent information and additional outcomes - risk of LRR, distant metastasis (DM) and SP - using different underlying models.

Methods Patient-, tumor- and treatment-related characteristics of all female patients diagnosed with invasive adenocarcinoma of the breast in 2007, 2008 and 2012, of who active 5-year follow-up was performed, were selected from the Netherlands Cancer Registry. Models were developed for LRR, DM and SP as a first event separately, and for each three-monthly time interval to predict time-dependent risks as accurately as possible. Follow-up was calculated from date of definite surgery to date of event or last observation. We compared three different models to estimate the three outcomes: a Cox regression model, a flexible parametric spline model and a random survival forest (RF) model. To assess calibration of each outcome, three-monthly risk predictions during the 5-year follow-up period were compared to corresponding observed event rates. To assess discrimination, the areas under the curves (AUC) were calculated for each timeframe in the 5-year period and averaged to one combined measure (average 5-year AUC). To correct for optimism we performed bootstrapping on the entire cohort with 200 replicates and updated the calibration measures and AUCs accordingly.

Results In total, 13,494 patients were included. LRR, DM and SP within five years were experienced by 2.8%, 6.3% and 3.1% of the patients, respectively. The following variables were included in the final models: age, tumor grade, tumor stage, nodal stage, multifocality, HER2 status, hormonal receptor status, type of surgery, chemotherapy, radiotherapy, hormonal therapy, anti-HER2 therapy. The optimism-corrected mean time-dependent prediction errors for individual risk predictions ranged between 0.12% and 0.46% for all three models and all three month timeframes. The average 5-year AUCs for LRR, SP and DM using the Cox model were 0.71, 0.63 and 0.77, respectively. The average 5-year AUCs for LRR, SP and DM using the parametric spline model were 0.71, 0.63 and 0.78, respectively. When using the RF model, the average 5-year AUCs were 0.74, 0.68 and 0.77 for LRR, SP and DM, respectively (Table).

Conclusion Although differences were very small, the RF model had the best performance overall. This INFLUENCE 2.0 model provides us with updated information on the individual time-dependent risks of LRR, DM and SP within five years following surgery. This model is freely accessible at https://tinyurl.com/influence-2 and can be used as an instrument to improve follow-up strategies and to give patients better insights in their prognosis.

Table. Optimism-corrected average AUCs over the 5-year follow-up periodModel typeLRDMSPCox regression0.710.770.63Flexible parametric spline0.710.780.63Random survival forest0.740.770.68

Citation Format: Sabine Siesling, Vinzenz Völkel, Tom Hueting, Teresa Draeger, Marissa C van Maaren, Luc JA Strobbe, Marjanka K Schmidt, Gabe S Sonke, Marjan van Hezewijk, Catharina GM Groothuis-Oudshoorn. Risk estimation of locoregional recurrence, distant metastasis and second primary breast cancer in early stage breast cancer patients: The INFLUENCE 2.0 nomogram [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-10.