Literature DB >> 9029856

Biological indices predictive of survival in 519 Italian terminally ill cancer patients. Italian Multicenter Study Group on Palliative Care.

M Maltoni1, M Pirovano, O Nanni, M Marinari, M Indelli, A Gramazio, E Terzoli, M Luzzani, F De Marinis, A Caraceni, R Labianca.   

Abstract

The knowledge of prognostic factors capable of subdividing cancer patients into groups having homogenous survival times is useful even in very advanced stages of illness. This prospective multicenter study assessed these prognostic factors in 530 terminal patients with solid tumors who were undergoing only palliative care. Thirteen hematological and urinary parameters were assessed on admission and every 28 days thereafter. In 519 assessable patients with a median survival of 32 days, six biological parameters demonstrated a statistically significant predictive prognosis. A poor prognosis was predicted by high total white blood count (WBC) (P < 0.0001), high neutrophil percentage (P < 0.0001), low lymphocyte percentage (P < 0.0001), low serum albumin level (P = 0.0015), low pseudocholinesterase level (P < 0.0001), and high proteinuria (P = 0.0064). Multiple regression analysis showed that only WBC, lymphocyte percentage and pseudocholinesterase level were independent predictors of survival. The individualization of biological parameters having an independent prognostic capacity is a useful step in the attempt to identify subsets of patients with a homogeneous prognosis. The biological factors needed are easily detected by means of a simple blood test and do not require invasive operations on patients who are already debilitated.

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Year:  1997        PMID: 9029856     DOI: 10.1016/s0885-3924(96)00265-5

Source DB:  PubMed          Journal:  J Pain Symptom Manage        ISSN: 0885-3924            Impact factor:   3.612


  21 in total

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Authors:  A M Jiménez-Gordo; J Feliu; B Martínez; J de-Castro; N Rodríguez-Salas; N Sastre; Y Vilches; E Espinosa; J R Rodríguez-Aizcorbe; M González-Barón
Journal:  Support Care Cancer       Date:  2008-06-05       Impact factor: 3.603

9.  Predicting survival time in noncurative patients with advanced cancer: a prospective study in China.

Authors:  Jing Cui; Lingjun Zhou; B Wee; Fengping Shen; Xiuqiang Ma; Jijun Zhao
Journal:  J Palliat Med       Date:  2014-04-07       Impact factor: 2.947

10.  A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer.

Authors:  Jui-Kun Chiang; Yu-Hsiang Cheng; Malcolm Koo; Yee-Hsin Kao; Ching-Yu Chen
Journal:  Jpn J Clin Oncol       Date:  2010-01-22       Impact factor: 3.019

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