Prognosis in Palliative Care Study (PiPS) predictor models were developed in 2011 to estimate the survival of terminal cancer patients in the United Kingdom. The aim of this study was to validate the PiPS model for terminal cancer patients in Korea, and evaluate its value in clinical practice.
This study included 202 advanced cancer patients who were admitted to the cancer hospital's palliative care ward from November 2011 to February 2013. On admission, physicians recorded the PiPS-A, PiPS-B, and doctor's survival estimates in inpatients.
The median survival across PiPS-A categories was 9, 28, and 33 days, and the median survival across PiPS-B was 9.5, 27, and 43 days. The median actual survival was 25 days; overall accuracy between the PiPS-A, PiPS-B, doctor's estimates of survival, and actual survival was 52.0%, 49.5%, and 46.5%, respectively. The PiPS-A and PiPS-B groups for survival in 'days' showed a sensitivity of 48.4% and 64.1%, and specificity of 87.7%, and 77.5%, respectively. The PiPS-A and PiPS-B groups for survival in 'weeks' showed a sensitivity of 59.2%, and 44.7%, and specificity of 61.6%, and 64.7%, respectively. The PiPS-A and PiPS-B 'months' group showed a sensitivity of 37.1% and 37.1%, and specificity of 74.9% and 78.4%, respectively. The 'weeks' and 'months' groups showed significantly prolonged survival rates than 'days' group did in both PiPS-A and PiPS-B, by the Kaplan-Meier method.
The PiPS predictor models effectively predicted the survival ≥14 days in terminal cancer patients, and were superior to doctor's estimates.
Cancer is one of the most critical public health problems globally. As of 2010, the total number of cancer-related deaths in Korea was 72,046, accounting for 28.2% of all deaths.
Previous studies have developed systematic and accurate prognostic models, including the palliative prognostic index (PPI),
The PiPS models were developed for patients in a palliative care service who were diagnosed with advanced cancers in the United Kingdom in 2011;
We evaluated advanced cancer patients who were admitted to the palliative care ward in Samsung Medical Center Cancer Hospital between November 1, 2011 and February 1, 2013. Of the 256 inpatients, 202 were included as subjects. Fifty patients lacking the records required for the PiPS models, and 4 patients who had undergone chemotherapy within the previous 1 month were excluded. Advanced cancers were defined as those that no longer responded to treatment and underwent progression.
On admission, clinicians recorded the PiPS prediction results, which were calculated using the PiPS prognosticator (
The PiPS-B model comprised diagnosis, symptoms, general health, and blood test results, which included white blood cell, neutrophils, lymphocytes, platelets, urea, alanine aminotransferase, alkaline phosphatase, albumin, and C-reactive protein, taken within 4 days of admission. In addition, the clinicians' estimates were recorded in order to compare to the PiPS predictions.
Data on the patients' age, sex, cancer treatment history, oxygen therapy, delirium, family support status, religion, and laboratory test results of hemoglobin, total bilirubin, and sodium were retrieved from the medical records. The family support status was assessed by a social worker of the hospital.
Actual survival time in days was defined as the time elapsed from admission to death. Patients who survived at the time of analysis (April 26, 2013) were regarded as censored data. Repetitive admissions were regarded as distinct admissions.
This study was performed in accordance with the institutional review board of the Samsung Medical Center, Seoul, Korea (IRB 2013-03-043).
The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the PiPS-A and the PiPS-B models in the prediction of survival were calculated for each of the 3 groups ('days,' 'weeks,' and 'months' groups). We estimated the overall accuracy levels to compare the PiPS and clinician's predictions against actual survival.
The Kaplan-Meier curve analysis and log-rank tests were used to compare the survival between the 3 groups of the PiPS-A and the PiPS-B models; P-values were corrected by Bonferroni's method due to multiple comparisons. All statistical assessments were considered significant when P < 0.05. Statistical analysis was performed using IBM SPSS ver. 21.0 (IBM Co., Armonk, NY, USA) and SAS ver. 9.3 (SAS Institute Inc., Cary, NC, USA).
Of the 202 patients, 195 (96.5%) died during the study period. Seven patients survived and were considered censored data.
Patients' characteristics are shown in
The most frequent primary cancer was colorectal cancer (19.3%), followed by gastric (16.8%), and pancreatic cancers (9.9%). Liver metastasis alone was noted in 39.1%, bone metastasis alone in 14.9%, both liver and bone metastases in 12.4%, and no metastasis in 33.6% of patients.
Most of the patients (90.1%) received anticancer treatment. Of these patients, 46 (22.8%) were treated with surgery, chemotherapy, and radiotherapy, 44 (21.8%) were treated with chemotherapy alone, 12 (5.9%) were treated with surgery, and 4 (2.0%) were treated with radiotherapy alone. Forty patients (19.8%) were treated with surgery and chemotherapy, 21 patients (10.4%) with chemotherapy and radiotherapy, 15 patients (7.4%) with surgery and radiotherapy. Twenty patients (9.9%) did not receive any treatments.
Fatigue was present in 90.6%, anorexia in 73.8%, weight loss in the previous month in 59.4%, dyspnea in 31.7%, dysphagia in 30.2%, and delirium in 10.9% of the patients. A mental test score of ≤3, which indicates poor cognitive function, was noted in 26.7%. Oxygen therapy was needed in 32%, and the mean pulse rate was 96.7 per minute (
An ECOG score of 3 was recorded in 51.0%, and 4 in 30.7% of the patients. Approximately two-thirds of the patients had a global health status score between 3 to 5 points.
In the PiPS-A prediction of survival, the number of patients and median survival were 48 (23.8%) and 9 days (95% CI, 7 to 13), respectively, in the 'days' group; similarly, there were 99 patients (49.0%) and 28 days (95% CI, 22 to 34), in the 'weeks' group, and 55 patients (27.2%) and 33 days (95% CI, 27 to 45), in the 'months' group. For the PiPS-B prediction models of survival, the number of patients and median survival were 72 (35.6%) and 9.5 days (95% CI, 8 to 15), respectively, in the 'days' group; Similarly, there were 81 patients (40.1%) and 27 days (95% CI, 23 to 34), in the 'weeks' group, and 49 patients (24.3%) and 43 days (95% CI, 32 to 48), in the 'months' group.
For the clinicians' estimates of survival, the number of patients and median survival were 32 (15.8%) and 9 days (95% CI, 5 to 12), respectively, in the 'days' group; similarly, there were 118 patients (58.4%) and 23 days (95% CI, 16 to 30), in the 'weeks' group and 52 patients (25.8%) and 39 days (95% CI, 30 to 48), in the 'months' group.
The actual survival data were as follows. In the 'days' group, 64 patients (31.7%) survived with a median survival of 7 days (95% CI, 5 to 8). In the 'weeks' group, 103 patients (51.0%) survived with a median survival of 30 days (95% CI, 27 to 34), and in the 'months' group, 35 patients (17.3%) survived with a survival of 84 days (95% CI, 75 to 116) (
The sensitivity, specificity, PPV, and NPV of the PiPS-A and PiPS-B models were calculated for the 3 groups (
In the prediction of survival, the PiPS-B model showed a sensitivity of 64.1%, a specificity of 77.5%, a PPV of 56.9%, and an NPV of 43.1% for the 'days' group; a sensitivity of 44.7%, a specificity of 64.7%, a PPV of 56.8%, and an NPV of 43.2% for the 'weeks' group; a sensitivity of 37.1%, a specificity of 78.4%, a PPV of 26.5%, and an NPV of 73.5% for the 'months' group.
The overall accuracy between the PiPS-A prediction and actual survival was 52.0%. The overall accuracy between PiPS-B prediction and actual survival was 49.5%. The overall accuracy between clinicians' estimates and actual survival was 46.5%, which were lower than those of the PiPS models.
Kaplan-Meier survival curves of the PiPS-A and PiPS-B models in the 3 groups are shown in
In the 'days' and 'weeks' groups, the PiPS-A/PiPS-B predictions and clinicians' estimates were consistent with actual median survival. However, in the 'months' group, where the PiPS-A/PiPS-B predictions and clinicians' estimates were 14 to 55 days, 17.3% of the patients in our study were included in the 'months' group, compared to 40% of the patients in the original study.
The PiPS-B scores, which included laboratory results, predicted shorter than actual survival times. The PiPS-B prediction of survival was the most accurate in the 'days' group (35.6%), while clinicians' estimates were the least accurate in the 'days' group (15.8%). These results demonstrate that advanced cancer patients' laboratory results are abnormal due to acute symptoms and long course of the disease on admission. Previous studies have reported that clinicians overestimate survival times.
The sensitivity, specificity, PPV, and NPV of predictions of survival using the PiPS-A and the PiPS-B predictor models were variable. Using the PiPS-A and the PiPS-B scales, the 'weeks' and 'months' groups showed significantly prolonged survival than the 'days' group, as measured by the Kaplan-Meier method. Although there was no significant difference between the 'weeks' and 'months' groups, our results suggest that the PiPS predictor models were useful for predicting whether advanced cancer patients could survive for more than 14 days. The PiPS-A model, which comprises diagnosis, symptoms, and general health, is non-invasive and useful when laboratory results are unavailable. Although the PiPS-B model, which includes blood test results, can objectively predict patient's condition, it predicted shorter than actual survival times in our study. In cancer hospitals, these laboratory results may be influenced by the treatment to manage acute symptoms.
There have been no previous reports on the validation of the PiPS predictor models in literature; in contrast, the PPI model has been validated in many countries.
With the exception of weight loss in the previous month, anorexia, dyspnea, dysphagia, fatigue, decreased cognitive function, and increased pulse rate occurred with greater frequency in the present study than in the original study.
The results of the present study are subject to some limitations. First, the generalizability of our results is limited because the present study included only inpatients in the palliative care ward of a cancer hospital, excluding outpatients and other patients from various care systems, including hospices, and home and community care systems. Further research remains to be conducted, in order to generalize the findings for advanced cancer patients in various settings. Second, it is difficult to accurately predict survival due to some fluctuations in symptoms and laboratory results after treatment. Most patients were admitted to our palliative care ward to manage acute symptoms, and we used the laboratory results obtained within 4 days of admission. Third, the 'months' group of the present study was smaller than that reported in the original study.
Despite these limitations, the present study was the first to evaluate the PiPS model, and has provided a basis for applying the findings to Korean advanced cancer inpatients. The PiPS prediction models of survival were superior to clinician's estimates. The results of this study suggest that accurate prediction of survival may require comprehensive prognostic tools that which include clinicians' estimates. The PiPS predictor models are useful for predicting whether advanced cancer patients will survive for more than 14 days. Further studies on long-term survival prediction and comparisons of accuracy of several prognostic tools are needed to develop more relevant prognostic factors in order to contribute to palliative care.
No potential conflict of interest relevant to this article was reported.
Kaplan-Meier survival curves of the three prognostic groups categorized by PiPS-A scores. Kaplan-Meier survival curves of the three prognostic groups categorized by PiPS-A scores: log rank test and P-values were corrected by Bonferroni's method. Solid line: days group, big dotted line: weeks group, small dotted line: months group. P = 0.018 between the 'days' and 'weeks' groups; P < 0.001 between the 'days' and 'months' groups; P = 0.183 between the 'weeks' and 'months' groups. PiPS: Prognosis in Palliative Care Study.
Kaplan-Meier survival curves of the three prognostic groups categorized by PiPS-B scores. Kaplan-Meier survival curves of the three prognostic groups categorized by the PiPS-B scores: log rank test and P-values were corrected by Bonferroni's method. Solid line: 'days' group, big dotted line: 'weeks' group, small dotted line: 'months' group. P < 0.001 between the 'days' and 'weeks' groups; P < 0.001 between the 'days' and 'months' groups; P = 0.114 between the 'weeks' and 'months' groups. PiPS: Prognosis in Palliative Care Study.
Characteristics of patients (n = 202)
Values are presented as number (%), mean ± SD, or median (95% confidence interval).
*Intrathoracic, pharynx, esophagus, biliary, genitourinary, brain, musculoskeletal, skin, blood and immune system, nervous system. †Liver and bone metastasis. ‡Chemotherapy, radiotherapy, and surgery.
Symptoms, signs, and laboratory results of patients
Values are presented as number (%) or mean ± SD.
*Abbreviated mental test score. †A study-specific seven-point scale. ‡Available within four days of study entry.
Distribution of PiPS-A, PiPS-B, and doctors' survival predictions against actual survival durations
PiPS: Prognosis in Palliative Care Study.
Accuracy of PiPS and doctors' predictions
Values are presented as %.
PiPS: Prognosis in Palliative Care Study.