Why Breast-Conserving Therapy Should be Considered Treatment of Choice in Early-Stage Breast Cancer Patients

Risk Factors for Unplanned Reoperation during the Expansion Phase in Two-Stage Breast Reconstruction in the Dutch Breast Implant Registry

BACKGROUND

The majority of postmastectomy breast reconstructions (PMBRs) are currently performed in two stages using a tissue expander (TE). However, complications during the expansion phase occur regularly, leading to unplanned reoperations and/or reconstruction failure. This study aimed to identify risk factors for unplanned reoperation after TE placement, assessed the time until unplanned and planned reoperation, and investigated indications for unplanned reoperation.

METHODS

Patient- and surgery-related characteristics of patients who underwent two-stage PMBR between 2017 and 2021 were collected from the Dutch Breast Implant Registry (DBIR). Unplanned reoperation was defined as TE explantation followed by either no replacement or replacement with the same or a different TE. Covariate-adjusted characteristics associated with unplanned reoperation were determined using backward stepwise selection and multivariable logistic regression analyses.

RESULTS

In total, 2529 patients (mean age, 50.2 years) were included. Unplanned reoperation occurred in 19.4% of all registered TEs ( n = 3190). Independent factors associated with unplanned reoperation were body mass index (BMI) greater than or equal to 25 kg/m 2 (adjusted OR [aOR], 1.63, 99% CI, 1.20 to 2.57 for BMI of 25 to 29.9 kg/m 2 ; aOR, 2.57, 99% CI, 1.74 to 3.78 for BMI ≥30 kg/m 2 ), low institutional volume (aOR, 1.51; 99% CI, 1.06 to 2.18), no drains (aOR, 2.06; 99% CI, 1.15 to 3.60), subcutaneous TE placement (aOR, 5.71; 99% CI, 3.59 to 9.10), and partial pectoralis major muscle coverage (aOR, 1.35; 99% CI, 1.02 to 1.79). Age younger than 40 years (aOR, 0.49; 99% CI, 0.32 to 0.74) and delayed PMBR (aOR, 0.35; 99% CI, 0.19 to 0.60) reduced the risk of unplanned reoperation. Median time until reoperation was 97 days for unplanned and 213 days for planned reoperation. Deep wound infections were most often registered as indication for unplanned reoperation (34.4%).

CONCLUSION

This study identified several risk factors for unplanned reoperation that may be used to reduce complications in expander-based PMBR.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Risk, III.

Triple-negative breast cancer survival prediction: population-based research using the SEER database and an external validation cohort

Introduction

Triple-negative breast cancer (TNBC) is linked to a poorer outlook, heightened aggressiveness relative to other breast cancer variants, and limited treatment choices. The absence of conventional treatment methods makes TNBC patients susceptible to metastasis. The objective of this research was to assess the clinical and pathological traits of TNBC patients, predict the influence of risk elements on their outlook, and create a prediction model to assist doctors in treating TNBC patients and enhancing their prognosis.

Methods

We included 23,394 individuals with complete baseline clinical data and survival information who were diagnosed with primary TNBC between 2010 and 2015 based on the SEER database. External validation utilised a group from The Affiliated Lihuili Hospital of Ningbo University. Independent risk factors linked to TNBC prognosis were identified through univariate, multivariate, and least absolute shrinkage and selection operator regression methods. These characteristics were chosen as parameters to develop 3- and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) nomogram models. Model accuracy was assessed using calibration curves, consistency indices (C-indices), receiver operating characteristic curves (ROCs), and decision curve analyses (DCAs). Finally, TNBC patients were divided into groups of high, medium, and low risk, employing the nomogram model for conducting a Kaplan-Meier survival analysis.

Results

In the training cohort, variables such as age at diagnosis, marital status, grade, T stage, N stage, M stage, surgery, radiation, and chemotherapy were linked to OS and BCSS. For the nomogram, the C-indices stood at 0.762, 0.747, and 0.764 in forecasting OS across the training, internal validation, and external validation groups, respectively. Additionally, the C-index values for the training, internal validation, and external validation groups in BCSS prediction stood at 0.793, 0.755, and 0.811, in that order. The findings revealed that the calibration of our nomogram model was successful, and the time-variant ROC curves highlighted its effectiveness in clinical settings. Ultimately, the clinical DCA showcased the prospective clinical advantages of the suggested model. Furthermore, the online version was simple to use, and nomogram classification may enhance the differentiation of TNBC prognosis and distinguish risk groups more accurately.

Conclusion

These nomograms are precise tools for assessing risk in patients with TNBC and forecasting survival. They can help doctors identify prognostic markers and create more effective treatment plans for patients with TNBC, providing more accurate assessments of their 3- and 5-year OS and BCSS.