Development and Validation of a Bedside Score to Predict Early Death in Cancer of Unknown Primary Patients

Nicolas Penel, Sylvie Negrier, Isabelle Ray-Coquard, Charles Ferte, Patrick Devos, Antoine Hollebecque, Michael B Sawyer, Antoine Adenis and Pascal Seve

PLOS ONE, 2009, vol. 4, issue 8, 1-6

Abstract: 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×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.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0006483

DOI: 10.1371/journal.pone.0006483

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