The aim of this work was to validate a previously constructed prognostic score for terminally ill cancer patients in order to determine its value in clinical practice. The Palliative Prognostic Score (PaP Score) was tested on a population of 451 evaluable patients consecutively entered in the hospice programs of 14 Italian Palliative Care Centers. The score subdivided patients into three specific risk classes based on the following six predictive factors of death: dyspnea, anorexia, Karnofsky Performance Status (KPS), Clinical Prediction of Survival (CPS), total white blood count (WBC), and lymphocyte percentage. The performance of the PaP Score index in the training and testing sets was evaluated by comparing mortality rates in the 3 prognostic risk categories. The score was able to subdivide the validation-independent case series into three risk groups. Median survival was 76 days in group A (with a 86.6% probability of 30-day survival), 32 days in group B (with a 51.6% probability of 30-day survival), and 14 days in group C (with a 16.9% probability of 30-day survival). Survival medians were remarkably similar to those of the training set (64 days in group A, 32 days in group B, and 11 days in group C). In the complex process of staging terminally ill patients, the PaP Score is a simple instrument which permits a more accurate quantification of expected survival. It has been validated on an independent case series and is thus suitable for use in clinical practice.

Background. The individualization of prognostic factors in the various stages of cancer facilitates the planning of a therapeutic assistance program aimed at various subsets of patients. The prognostic factors for survival in patients terminally ill with cancer have been investigated in case studies that are often retrospective, monocentric and/or include a mixture of patients in advanced disease stages. The aim of this prospective multicentric study was to verify those clinical factors predictive of survival in a population of patients with terminal cancer. Methods. This prospective and multicentric study was performed on 540 patients with solid tumors in the disseminated phase, no longer subject to specific therapy. Patients were evaluated at study entry and every 4 weeks thereafter. The analysis was performed for 23 clinical parameters. Results. Of 530 assessable patients with a median survival of 32 days, 15 factors were found to be statistically significant prognostic factors. By univariate analysis, 13 factors were found to be indicators of a worse survival: age older than 65 years (P = 0.05); palliative corticosteroid treatment (P < 0.001), anorexia (P < 0.001); dry mouth (P < 0.001); dysphagia (P < 0.001); hospitalization (P < 0.001); transfusion (P < 0.001); weight loss greater than or equal to 10% (P = 0.001); dyspnea (P = 0.01); pain (P = 0.006); increasing amount of pain‐killer treatment (P = 0.01); increasing number of symptoms (P < 0.001); and worse clinical prediction of survival (P < 0.001). Two factors that correlated with a better survival rate were palliative progestin treatment (P = 0.03) and a higher Karnofsky performance status (P < 0.001). Multiple regression.

In recent years, extensive research has been performed to identify prognostic factors that predict survival in terminally ill cancer patients. This study describes the construction of a simple prognostic score based on factors identified in a prospective multicenter study of 519 patients with a median survival of 32 days. An exponential multiple regression model was adopted to evaluate the joint effect of some clinico-biological variables on survival. From an initial model containing 36 variables, a final parsimonious model was obtained by means of a backward selection procedure. The Palliative Prognostic Score (PaP Score) is based on the final model and includes the following variables: Clinical Prediction of Survival (CPS), Karnofsky Performance Status (KPS), anorexia, dyspnea, total white blood count (WBC) and lymphocyte percentage. A numerical score was given to each variable, based on the relative weight of the independent prognostic significance shown by each single category in the multivariate analysis. The sum of the single scores gives the overall PaP Score for each patient and was used to subdivide the study population into three groups, each with a different probability of survival at 30 days: (1) group A: probability of survival at 30 days > 70%, with patient score < or = 5.5; (2) group B: probability of survival at 30 days 30-70%, with patient score 5.6-11.0; and (3) group C: probability of survival at 30 days < 30%, with patient score > 11.0. Using this method, 178/519 (34.3%) patients were classified in risk group A, 205 (39.5%) patients were in risk group B, and 136 (26.2%) patients were in risk group C. The patients classified in the three risk groups had a very different survival experience (logrank = 294.8, P < 0.001), with a median survival of 64 days for group A, 32 days for group B, and 11 days for group C. The PaP Score based on simple clinical and biohumoral variables proved to be statistically significant in a multivariate analysis. The score is valid in this population (training set). An independent validation on another patient series (testing set) is required and is the object of a companion paper.

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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