A nomogram to predict individual prognosis in node-negative breast carcinoma.
BACKGROUND
Currently, the benefit of chemotherapy (CT) in node-negative breast carcinoma (NNBC) is discussed. The evaluation of classical clinical and histological factors is limited to assess individual outcome. A statistical model was developed to improve the prognostic accuracy of NNBC.


METHODS
A total of 305 node-negative breast carcinomas who underwent surgery (+/- radiotherapy) but no adjuvant treatment were selected. Putative prognosis factors including age, tumour size, oestrogen receptor (ER), progesterone receptor (PgR), Scarff-Bloom-Richardon (SBR) grading, urokinase plasminogen activator (uPA), plasminogen activator inhibitor 1 (PAI-1) and thymidine kinase (TK) were evaluated. The developed model was internally validated using Harrell's concordance index. A prognosis index (PI) was proposed and compared with Adjuvant! Online program.


RESULTS
Age (p < 0.001), pathological tumour size (pT) (p < 0.001), PgR (p = 0.02), and PAI-1 (p ≤ 0.001) were included in the Cox regression model predicting Breast cancer specific survival (BCSS) at 5-years. Internal validation revealed a concordance index of 0.71. A PI score was derived from our nomogram. The PI score was significantly associated with BCSS (hazard ratio (HR): 4.1 for intermediate, p=0.02, HR: 8.8, p < 0.001 for high group) as compared to Adjuvant! Online score (HR: 1.4, p=0.14).


CONCLUSIONS
A nomogram can be used to predict probability survival curves for individual breast cancer patients.
Laboratoire de transfert d'oncologie biologique, Assistance Publique - Hôpitaux de Marseille, Faculté de Médecine Nord, Marseille, France. chafika.mazouni@igr.fr
C
C
Mazouni
F
F
Spyratos
S
S
Romain
F
F
Fina
P
P
Bonnier
L H
LH
Ouafik
P M
PM
Martin
D000367:Age Factors; D014408:Biomarkers, Tumor / Q000032:analysis; D001943:Breast Neoplasms / Q000737:chemistry / Q000401:mortality / Q000473:pathology / Q000601:surgery*; D002277:Carcinoma / Q000737:chemistry / Q000401:mortality / Q000473:pathology / Q000601:surgery*; D017024:Chemotherapy, Adjuvant; D003661:Decision Support Techniques; D018572:Disease-Free Survival; D005260:Female; D005602:France; D006801:Humans; D053208:Kaplan-Meier Estimate; D008197:Lymph Node Excision; D008198:Lymph Nodes / Q000473:pathology*; D015411:Mastectomy, Modified Radical / Q000009:adverse effects / Q000401:mortality; D015412:Mastectomy, Segmental / Q000009:adverse effects / Q000401:mortality; D008875:Middle Aged; D015999:Multivariate Analysis; D049451:Nomograms; D018579:Patient Selection; D017395:Plasminogen Activator Inhibitor 1 / Q000032:analysis; D016016:Proportional Hazards Models; D018714:Radiotherapy, Adjuvant; D011980:Receptors, Progesterone / Q000032:analysis; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome; D047368:Tumor Burden
D014408:Biomarkers, Tumor; D017395:Plasminogen Activator Inhibitor 1; D011980:Receptors, Progesterone; C051321:SERPINE1 protein, human