Prognostic markers in node-negative breast cancer: a prospective study.
BACKGROUND
Despite years of research, it is still unclear which women with node-negative (N-) breast cancer will need adjuvant chemotherapy and which women are being treated unnecessarily. Our goal was to determine which factors best predicted disease free survival (DFS) or cancer-specific overall survival (OS) and, therefore, select the correct patients for treatment. A total of 11 parameters were measured: estrogen receptor (ER), progesterone receptor (PR), age, race, ploidy status, %G0/G1 (% non-DNA synthesis), %S (% S-phase), cathepsin D status, size, stage, and histologic grade.


RESULTS
In this prospective study, we followed 556 N- patients diagnosed between 1991 and 1996. The tumors were 56% ER+, 51% PR+, 30% diploid, with a mean %S of 8.9%. The level of cathepsin D ranged from 0.50 to 155 pmol/mg of protein with a mean of 42.9 pmol/mg of protein. There were 87 recurrences (16%) and 72 cancer deaths (13%), with a median follow-up of 7.8 years. Ploidy status (p = 0.01), S-phase activity (p = 0.003), G1 phase activity (p = 0.02) and age (p = 0.01) were able to significantly predict DFS in a univariate manner. All of the measurable factors were significant or borderline significant in predicting OS in a univariate manner except for age, race, and ER status. In multivariate analysis with S-phase included, it was the only remaining factor in DFS and OS; with S-phase excluded, age and ploidy status remained as factors for DFS in stepwise regression, while PR, size, and cathepsin D were the remaining factors that predicted cancer-specific OS. The effect of adjuvant treatment on prognosis was also analyzed.


CONCLUSIONS
Both biochemical and clinical parameters have the potential to predict prognosis for N- breast cancer. In this large prospective clinical trial, with a median follow-up of 7.8 years, no individual marker adequately predicted the prognosis for an individual patient. %S activity was the best independent marker, but only 77% of the tumors provided this value. Subset analysis provided improved prognostication, but there were limits to its utility. These data represents a definitive study starting in 1991 and ending in 2002.
Kute
T E
TE
Department of Pathology, Wake Forest University School of Medicine, Winston-Salem, North Carolina 27157-1072, USA. tkute@wfubmc.edu
Russell
G B
GB
Zbieranski
N
N
Long
R
R
Johnston
S
S
Williams
H
H
Stackhouse
C
C
Wilkins
L
L
Evans
I
I
Berry
P
P
Rimmer
K
K
Tucker
E
E
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality / Q000473:pathology; D056649:Cathepsin G; D002403:Cathepsins / Q000032:analysis*; D002453:Cell Cycle; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D008875:Middle Aged; D015999:Multivariate Analysis; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality / Q000473:pathology; D011003:Ploidies; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D012697:Serine Endopeptidases
D014408:Biomarkers, Tumor; D002403:Cathepsins; D012697:Serine Endopeptidases; C534094:CTSG protein, human; D056649:Cathepsin G