Development and validation of a bedside score to predict early death in cancer of unknown primary patients.
BACKGROUND
We have investigated predictors of 90-day-mortality in a large cohort of non-specific cancer of unknown primary patients.


METHODS
Predictors have been identified by univariate and then logistic regression analysis in a single-center cohort comprising 429 patients (development cohort). We identified four predictors that produced a predictive score that has been applied to an independent multi-institutional cohort of 409 patients (validation cohort). The score was the sum of predictors for each patient (0 to 4).


RESULTS
The 90-day-mortality-rate was 33 and 26% in both cohorts. Multivariate analysis has identified 4 predictors for 90-day-mortality: performance status>1 (OR = 3.03, p = 0.001), at least one co-morbidity requiring treatment (OR = 2.68, p = 0.004), LDH>1.5 x the upper limit of normal (OR = 2.88, p = 0.007) and low albumin or protein levels (OR = 3.05, p = 0.007). In the development cohort, 90-day-mortality-rates were 12.5%, 32% and 64% when the score was [0-1], 2 and [3]-[4], respectively. In the validation cohort, risks were 13%, 25% and 62% according to the same score values.


CONCLUSIONS
We have validated a score that is easily calculated at the beside that estimates the 90-days mortality rate in non-specific CUP patients. This could be helpful to identify patients who would be better served with palliative care rather than aggressive chemotherapy.
Penel
Nicolas
N
Département de Cancérologie Générale, Centre Oscar Lambret, Lille, France. n-penel@o-lambret.fr
Negrier
Sylvie
S
Ray-Coquard
Isabelle
I
Ferte
Charles
C
Devos
Patrick
P
Hollebecque
Antoine
A
Sawyer
Michael B
MB
Adenis
Antoine
A
Seve
Pascal
P
D015331:Cohort Studies; D006801:Humans; D015999:Multivariate Analysis; D009382:Neoplasms, Unknown Primary / Q000401:mortality* / Q000503:physiopathology; D016019:Survival Analysis