Validation of the PREDICT Prognostication Tool in US Patients With Breast Cancer.


Journal

Journal of the National Comprehensive Cancer Network : JNCCN
ISSN: 1540-1413
Titre abrégé: J Natl Compr Canc Netw
Pays: United States
ID NLM: 101162515

Informations de publication

Date de publication:
10 2023
Historique:
received: 04 04 2023
accepted: 20 06 2023
medline: 30 10 2023
pubmed: 19 10 2023
entrez: 19 10 2023
Statut: ppublish

Résumé

PREDICT is an online prognostication tool derived from breast cancer registry information on approximately 6,000 women treated in the United Kingdom that estimates the postsurgical treatment benefit of surgery alone, chemotherapy, trastuzumab, endocrine therapy, and/or adjuvant bisphosphonates in early-stage breast cancer. Our aim was to validate the PREDICT algorithm in predicting 5- and 10-year overall survival (OS) probabilities using real-world outcomes among US patients with breast cancer. A retrospective study was performed including women diagnosed with unilateral breast cancer in 2004 through 2012. Women with primary unilateral invasive breast cancer were included. Patients with bilateral or metastatic breast cancer, no breast surgery, or missing critical clinical information were excluded. Prognostic scores from PREDICT were calculated and external validity was approached by assessing statistical discrimination through area under time-dependent receiver-operator curves (AUC) and comparing the predicted survival to the observed OS in relevant subgroups. We included 708,652 women, with a median age of 58 years. Most patients were White (85.4%), non-Hispanic (88.4%), and diagnosed with estrogen receptor-positive breast cancer (79.6%). Approximately 50% of patients received adjuvant chemotherapy, 67% received adjuvant endocrine therapy, 60% underwent a partial mastectomy, and 59% had 1 to 5 axillary sentinel nodes removed. Median follow-up time was 97.7 months. The population's 5- and 10-year OS were 89.7% and 78.7%, respectively. Estimated 5- and 10-year median survival with PREDICT were 88.3% and 73.8%, and an AUC of 0.77 and 0.76, respectively. PREDICT performed most poorly in patients with high Charlson-Deyo comorbidity scores (2-3), where PREDICT overestimated OS. Sensitivity analysis by year of diagnosis and HER2 status showed similar results. In this prognostic study utilizing the National Cancer Database, the PREDICT tool accurately predicted 5- and 10-year OS in a contemporary and diverse population of US patients with nonmetastatic breast cancer.

Sections du résumé

BACKGROUND
PREDICT is an online prognostication tool derived from breast cancer registry information on approximately 6,000 women treated in the United Kingdom that estimates the postsurgical treatment benefit of surgery alone, chemotherapy, trastuzumab, endocrine therapy, and/or adjuvant bisphosphonates in early-stage breast cancer. Our aim was to validate the PREDICT algorithm in predicting 5- and 10-year overall survival (OS) probabilities using real-world outcomes among US patients with breast cancer.
METHODS
A retrospective study was performed including women diagnosed with unilateral breast cancer in 2004 through 2012. Women with primary unilateral invasive breast cancer were included. Patients with bilateral or metastatic breast cancer, no breast surgery, or missing critical clinical information were excluded. Prognostic scores from PREDICT were calculated and external validity was approached by assessing statistical discrimination through area under time-dependent receiver-operator curves (AUC) and comparing the predicted survival to the observed OS in relevant subgroups.
RESULTS
We included 708,652 women, with a median age of 58 years. Most patients were White (85.4%), non-Hispanic (88.4%), and diagnosed with estrogen receptor-positive breast cancer (79.6%). Approximately 50% of patients received adjuvant chemotherapy, 67% received adjuvant endocrine therapy, 60% underwent a partial mastectomy, and 59% had 1 to 5 axillary sentinel nodes removed. Median follow-up time was 97.7 months. The population's 5- and 10-year OS were 89.7% and 78.7%, respectively. Estimated 5- and 10-year median survival with PREDICT were 88.3% and 73.8%, and an AUC of 0.77 and 0.76, respectively. PREDICT performed most poorly in patients with high Charlson-Deyo comorbidity scores (2-3), where PREDICT overestimated OS. Sensitivity analysis by year of diagnosis and HER2 status showed similar results.
CONCLUSIONS
In this prognostic study utilizing the National Cancer Database, the PREDICT tool accurately predicted 5- and 10-year OS in a contemporary and diverse population of US patients with nonmetastatic breast cancer.

Identifiants

pubmed: 37856198
doi: 10.6004/jnccn.2023.7048
doi:

Substances chimiques

Receptor, ErbB-2 EC 2.7.10.1

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1011-1019.e6

Commentaires et corrections

Type : CommentIn

Auteurs

Nickolas Stabellini (N)

1Case Western Reserve University School of Medicine, Cleveland, Ohio.
2Faculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, Brazil.
3Division of Hematology and Oncology, Department of Medicine, University Hospitals Seidman Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio.

Lifen Cao (L)

3Division of Hematology and Oncology, Department of Medicine, University Hospitals Seidman Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio.

Christopher W Towe (CW)

4Division of Thoracic and Esophageal Surgery, Department of Surgery, University Hospitals Seidman Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio.
5University Hospitals Research in Surgical Outcomes and Effectiveness (UH-RISES), Cleveland, Ohio.

Megan E Miller (ME)

5University Hospitals Research in Surgical Outcomes and Effectiveness (UH-RISES), Cleveland, Ohio.
6Division of Surgical Oncology, Department of Surgery, University Hospitals Seidman Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio.

Artur H Sousa-Santos (AH)

2Faculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, Brazil.

Amanda L Amin (AL)

5University Hospitals Research in Surgical Outcomes and Effectiveness (UH-RISES), Cleveland, Ohio.
6Division of Surgical Oncology, Department of Surgery, University Hospitals Seidman Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio.

Alberto J Montero (AJ)

1Case Western Reserve University School of Medicine, Cleveland, Ohio.
3Division of Hematology and Oncology, Department of Medicine, University Hospitals Seidman Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio.

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