Text Correction
A Fine–Gray analysis was missing in the original version []. A correction has now been made to Materials and Methods, Section 2.7: Statistical Analyses, and to Results, Section 3.9: Clinical Variables and Outcomes, where the final paragraph describing the competing risk analysis has been added. Also, Table 4 has been included to effectively represent the results of the Fine–Gray analysis.
 
       
    
    Table 4.
    Competing risk analysis.
  
The corrected paragraph for Section 2.7 (Statistical Analyses) is given below:
The summary statistics, including means, medians, ranges, and standard deviations, were calculated for continuous variables; the categorical variables were summarized as proportions and confidence intervals (95% CIs). Significant differences among continuous variables for non-parametric distributions were assessed using the Mann–Whitney U test. The Chi-square test or Fisher’s exact test was used to determine statistically significant differences among categorical variables. The PFS and OS were analyzed using the Kaplan–Meier method, while the log-rank test evaluated the differences between subgroups. Univariable and multivariable analyses of the PFS and OS were performed using the Cox proportional hazards model. In addition, because death may preclude observation of progression, we conducted competing risks analyses with progression as the event of interest and death as the competing event. Cumulative incidence functions were estimated for each subgroup and compared using Gray’s test, and subdistribution hazard ratios (SHRs) with 95% CIs were derived from Fine–Gray regression (univariable and multivariable), adhering to the same two-sided significance threshold (p < 0.05). Statistical significance was predetermined at a p-value < 0.05 based on a two-sided test. The analyses were performed using SPSS version 26 (IBM Company, Armonk, NY, USA) and R statistical software version 4.1.1 (GPL Technologies, Burbank, CA, USA). Competing risks analyses were performed in R (package cmprsk).
The new content added in second paragraph for Section 3.9 (Clinical Variables and Outcomes) is given below:
Using the pooled M and UNS tumors as the reference, the immunomodulatory (IM) subtype showed an sHR of 0.25 (95 % CI 0.08–0.81, p = 0.021). All other subtypes mirrored the non-significant behavior reported in the KM and multivariable Cox models (Table 4).
The new Table 4 has been provided above.
The authors apologize for any inconvenience caused and state that the scientific conclusions remain unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.
Reference
- Rodríguez-Bautista, R.; Caro-Sánchez, C.H.; Cabrera-Galeana, P.; Alanis-Funes, G.J.; Gutierrez-Millán, E.; Ávila-Ríos, S.; Matías-Florentino, M.; Reyes-Terán, G.; Díaz-Chávez, J.; Villarreal-Garza, C.; et al. Immune Milieu and Genomic Alterations Set the Triple-Negative Breast Cancer Immunomodulatory Subtype Tumor Behavior. Cancers 2021, 13, 6256. [Google Scholar] [CrossRef] [PubMed]
| Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. | 
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
