Survival prediction allows physicians to provide appropriate advice to advanced cancer patients and their families at the end of life, such as for the discontinuation of antineoplastic therapy, the discontinuation of life support therapy, and the provision of comfort care [16]. Survival time has an important impact on choices made by patients in palliative care, such as the place of death, the mode of care, the financial planning, and the mode of farewell [17].

It is common for clinicians to make overly optimistic or pessimistic survival predictions for advanced patients [18, 19]. Survival time is determined by the interaction of multiple complex factors [20], especially at the end of life. Studies have shown that [5] the prognostic factors in patients with advanced disease are different from those in patients with early disease. The prognostic factors in patients with early disease are mainly related to clinicopathological classification and treatment methods, while those in patients with advanced disease are mainly related to clinical symptoms and signs, biochemical test results, physical status and other factors. In our study, the prognostic factors for survival time were screened from among demographic characteristics, PPS, FRAIL scale, Barthel index, symptoms, signs and laboratory examination. In the simple association analysis, significant differences in age group, PPS, FRAIL scale, Barthel index, edema, dyspnea, CPR and WBC count were found between the two groups. Multivariate analysis eliminated confounding factors and concluded that the PPS was associated with the risk of death within 14 days.

The PPS was developed based on the Karnofsky Performance Scale (KPS) and used to assess the functional performance of patients in palliative care. A meta-analysis of 17 studies confirmed that PPS is a strong predictor of survival in palliative care patients, but whether the results can be applied to patients of different races and from different countries needs to be confirmed by follow-up studies [21]. The tool can be used in both cancer and noncancer patients, and its content is relatively simple and easy to use. However, there is no unified standard for the cutoff point in each study. Survival estimates ranged from 1 to 3 days for patients with PPSs of 10% compared with 5 to 36 days for those with scores of 30%. In this study, PPSs of 10% and 20–30% accounted for a high proportion of deaths within 14 days, consistent with reports using PPSs of 40% as the cutoff point for referral to palliative care [22]. The difference is that the institution in our study was a tertiary palliative care institution, and PPS ≤ 30% was used as one of the indicators to predict death within 14 days. A PPS ≥ 40%, combined with other predictors, can be used as a criterion for the referral of patients to tertiary palliative care facilities.

Functional status is potentially associated with survival time [23]. The Barthel Index has been used to assess functional independence since 1965 and is widely used in elderly patients and patients with neurological diseases [24,25,26,27]. When applying the index in palliative care, patients with low scores or weekly decreases had poor prognoses, independent functioning of patients was assessed, and patients were guided to the selection of treatment and the place of death [28]. Neoplastic diseases affect daily living activities and instrumental activities of daily living and reduce the independence of elderly patients [29]. Among patients with advanced disease, those with a lower Barthel index had a lower palliative performance score and shorter survival time. Functional assessment by the Barthel index showed a high prevalence of severe impairment in performing basic ADLs [30]. In this study, 95.08% of the patients who died within 14 days were dependent, and 67.63% of the patients who survived more than 14 days were dependent.

Frailty was first applied to geriatric patients and is defined as [31] ‘a biologic syndrome of decreased reserve and resistance causing vulnerability to adverse outcomes’. Prefrailty and frailty were significantly associated with mortality for all age groups in men and women after adjustment for confounders [11]. More than half of elderly cancer patients meet the criteria for frailty or prefrailty [32], and 79.6% of elderly cancer patients meet the criteria for frailty [29]. Patients with frailty have decreased adaptability, which is associated with adverse events and increases the risk of mortality [11]. In a 10-year follow-up of people aged 30–79 years in China, the mortality of frail people was 36.7 per 1000 person-years for all-cause cancer and 6.9 per 1000 person-years for cancer. The risk of mortality in frail cancer patients was greater than that in nonfrail cancer patients in the < 50 years, 50–64 years and > 65 years age groups [12]. In our study, 96.72% of the cancer patients who died within 14 days were frail, while 78.41% of the patients who died after 14 days were frail.

The median survival time was 48 (33.71, 62.29) days in the nonfrail group and 15 (12.46, 17.54) days in the frail group. Patients in the frail group had a shorter survival time than patients in the nonfrail group at the end of life, suggesting that frailty may be one of the predictors of death at the end of life. However, in the multivariable analysis, frailty had little association with the risk of death within 14 days. The reason may be that patients in our study were at the end of life, and the survival time ranged from 1 to 170 days. The incidence of frailty in the 261 patients was 222 (87.0%). At the end of life, the prevalence of frailty was high in both groups. The relationship between frailty and the risk of death in patients at the end of life needs to be further confirmed by expanding the study population and extending the observation time.

The PPS, Barthel index, and Frail scale score overlapped for ambulation and activity. Finally, the PPS and Frail Scale were selected for multifactor evaluation. According to the Barthel index, disability accounted for 80.5% of the deaths and was more common in patients with a survival time ≤ 14 days. The prevalence of frailty and dependence was greater than that in the other groups, which was consistent with the correlation between frailty and the Barthel index.

Among the end-of-life factors, dyspnea, fatigue, intestinal obstruction, fatigue, disturbance of consciousness, pain, gastrointestinal bleeding, respiration and blood pressure, and blood oxygen saturation are related to survival [33, 34]. However, the present study suggested that only dyspnea and edema were significantly different between the two groups. The results suggested that there may be differences in the prediction of end-of-life survival time by symptoms and signs in different regions and populations. However, this needs to be further verified. Alanine transaminase, white blood count, C-reactive protein, platelet count, urea, lymphocyte count, neutrophil count, albumin, and alkaline phosphatase are laboratory indicators that have been associated with end-of-life outcomes [33, 35]. The abnormalities in CPR and WBC count in group A were greater than those in group B, which was likely related to the decline in immunity and multiple organ function in patients who died.

Age, PPS, FRAIL score, edema status, dyspnea status and white blood cell count were used in the multivariable analysis. These indicators are reliable and easy to assess. The results showed that age, FRAIL scale score, CPR, WBC count, edema and dyspnea had little contribution to the logistic regression equation, while PPS had a substantial contribution to the prediction of mortality risk within 14 days. The PPS has 5 items and 10 grades, including ambulation, activity evidence of disease, self-care, intake and consciousness level, to summarize the performance of patients at the end of life, which can be used to predict survival time. Our study was a single-center retrospective study with a small sample size. The study time could be extended, and the number of patients could be increased to further study the influence of frailty, PPS and other indicators on survival at the end of life.