The association of the palliative performance scale and hazard of death in an ambulatory cancer population

Prognoses Associated With Palliative Performance Scale Scores in Modern Palliative Care Practice

Importance

The Palliative Performance Scale (PPS) is one of the most widely used prognostic tools for patients with serious illness. However, current prognostic estimates associated with PPS scores are based on data that are over a decade old.

Objective

To generate updated prognostic estimates by PPS score, care setting, and illness category, and examine how well PPS predicts short- and longer-term survival.

Design, Setting, and Participants

This prognostic study was conducted at a large academic medical center with robust inpatient and outpatient palliative care practices using electronic health record data linked with data from California Vital Records. Eligible participants included patients who received a palliative care consultation between January 1, 2018, and December 31, 2020. Data analysis was conducted from November 2022 to February 2024.

Exposure

Palliative care consultation with a PPS score documented.

Main Outcomes and Measures

The primary outcomes were predicted 1-, 6-, and 12-month mortality and median survival of patients by PPS score in the inpatient and outpatient settings, and performance of the PPS across a range of survival times. In subgroup analyses, mortality risk by PPS score was estimated in patients with cancer vs noncancer illnesses and those seen in-person vs by video telemedicine in the outpatient setting.

Results

Overall, 4779 patients (mean [SD] age, 63.5 [14.8] years; 2437 female [51.0%] and 2342 male [49.0%]) had a palliative care consultation with a PPS score documented. Of these patients, 2276 were seen in the inpatient setting and 3080 were seen in the outpatient setting. In both the inpatient and outpatient settings, 1-, 6-, and 12-month mortality were higher and median survival was shorter for patients with lower PPS scores. Prognostic estimates associated with PPS scores were substantially longer (2.3- to 11.7-fold) than previous estimates commonly used by clinicians. The PPS had good ability to discriminate between patients who lived and those who died in the inpatient setting (integrated time-dependent area under the curve [iAUC], 0.74) but its discriminative ability was lower in the outpatient setting (iAUC, 0.67). The PPS better predicted 1-month survival than longer-term survival. Mortality rates were higher for patients with cancer than other serious illnesses at most PPS levels.

Conclusions and Relevance

In this prognostic study, prognostic estimates associated with PPS scores were substantially longer than previous estimates commonly used by clinicians. Based on these findings, an online calculator was updated to assist clinicians in reaching prognostic estimates that are more consistent with modern palliative care practice and specific to the patient's setting and diagnosis group.

Predictors of Mortality in Patients with Advanced Cancer-A Systematic Review and Meta-Analysis

To timely initiate advance care planning in patients with advanced cancer, physicians should identify patients with limited life expectancy. We aimed to identify predictors of mortality. To identify the relevant literature, we searched Embase, MEDLINE, Cochrane Central, Web of Science, and PubMed databases between January 2000-April 2020. Identified studies were assessed on risk-of-bias with a modified QUIPS tool. The main outcomes were predictors and prediction models of mortality within a period of 3-24 months. We included predictors that were studied in ≥2 cancer types in a meta-analysis using a fixed or random-effects model and summarized the discriminative ability of models. We included 68 studies (ranging from 42 to 66,112 patients), of which 24 were low risk-of-bias, and 39 were included in the meta-analysis. Using a fixed-effects model, the predictors of mortality were: the surprise question, performance status, cognitive impairment, (sub)cutaneous metastases, body mass index, comorbidity, serum albumin, and hemoglobin. Using a random-effects model, predictors were: disease stage IV (hazard ratio [HR] 7.58; 95% confidence interval [CI] 4.00-14.36), lung cancer (HR 2.51; 95% CI 1.24-5.06), ECOG performance status 1+ (HR 2.03; 95% CI 1.44-2.86) and 2+ (HR 4.06; 95% CI 2.36-6.98), age (HR 1.20; 95% CI 1.05-1.38), male sex (HR 1.24; 95% CI 1.14-1.36), and Charlson comorbidity score 3+ (HR 1.60; 95% CI 1.11-2.32). Thirteen studies reported on prediction models consisting of different sets of predictors with mostly moderate discriminative ability. To conclude, we identified reasonably accurate non-tumor specific predictors of mortality. Those predictors could guide in developing a more accurate prediction model and in selecting patients for advance care planning.

Changes in the palliative performance scale may be as important as the initial palliative performance scale for predicting survival in terminal cancer patients

OBJECTIVE

The accurate estimation of expected survival in terminal cancer patients is important. The palliative performance scale (PPS) is an important factor in predicting survival of hospice patients. The purpose of this study was to examine how initial status of PPS and changes in PPS affect the survival of hospice patients in Korea.

METHOD

We retrospectively examined 315 patients who were admitted to our hospice unit between January 2017 and December 2018. The patients were divided based on the PPS of ≥50% (group A) and ≤40% (group B). We performed survival analysis for factors associated with the length of survival (LOS) in group A. Based on the hospice team's weekly evaluation of PPS, we examined the effect of initial levels and changes in group A on the prognosis of patients who survived for 2 weeks or more.

RESULTS

At the time of admission to hospice, 265 (84.1%) patients were PPS ≥50%, and 50 (15.9%) were PPS ≤40%. The median LOS of PPS ≥50% and PPS ≤40% were 15 (2-158 days) and 9 (2-43 days), respectively. Male, gastrointestinal cancer, and lower initial PPS all predicted poor prognosis in group A. Male, gastrointestinal cancer, and a PPS change of 10% or greater, compared with initial status 1 week and 2 weeks of hospitalization, were all predictors of poor prognosis in group A patients who survived for 2 weeks or longer.

SIGNIFICANCE OF RESULTS

Our research demonstrates the significance of PPS change at 1 week and 2 weeks, suggesting the importance of evaluating not only initial PPS but also change in PPS.

Is Performance Status Associated with Symptom Scores?

Background: Symptom scores and performance status are both important measures for patients with cancer. However, since performance status is not often part of routinely collected data, there is interest in exploring whether it can be calculated from symptom scores. Methods: This was a population-based longitudinal study of cancer outpatients in Ontario, Canada in the year following their cancer diagnosis and among the subset of patients during the last year of their lives. Results: In the first year after diagnosis, there was a significant relationship between performance status and fatigue and appetite; fatigue and well-being had a significant association with performance status in the last year of life. In both periods, the associations, although statistically significant, were not large enough to be clinically meaningful. Conclusion: Performance status is an important measurement that cannot be substituted or captured with symptom scores; it is important for healthcare providers to record performance scores on a regular basis.

Initiation of Chemotherapy in Cancer Patients with Poor Performance Status: A Population-Based Analysis

Objective: Practice guidelines indicate that patients who have months to weeks left to live should not be offered chemotherapy. We examined factors associated with clinician-reported poor performance status as determined by the Palliative Performance Scale (PPS) and subsequent initiation of intravenous (IV) chemotherapy in an ambulatory cancer population in Ontario, Canada. Methods: In this retrospective study, patients who had at least one PPS assessment indicating poor performance status (a PPS score of 50 or lower) comprised the study cohort. Using linked administrative databases, we observed the cohort for initiation of IV chemotherapy within 30 days of the first (index) poor PPS assessment. Results: We excluded patients for whom IV or oral chemotherapy was on going or recently completed or whose performance status improved following the index assessment. Of the remaining cohort, 9.3 percent (264/2,842) received IV chemotherapy within 30 days of the index PPS. Conclusion: A small number of cancer patients with poor performance status began IV chemotherapy in the month following assessment.

Objectif: Les directives de pratiques cliniques recommandent que l'on ne propose pas de traitements de chimiothérapie aux patients présentant une espérance de survie de quelques semaines à quelques mois. Nous avons examiné, chez un groupe de patients atteints du cancer en Ontario, au Canada, les éléments associés au faible statut des malades selon les paramètres de l'Έchelle de performance pour soins palliatifs afin d'identifier les facteurs qui ont déterminé l'amorce de la chimiothérapie. Méthode: Cette étude rétrospective comprenait les patients chez qui lors du test d'évaluation de performance on avait noté au moins un élément négatif, soit un score de performance de 50 ou moins. En utilisant plusieurs banques de données administratives interreliées, nous avons étudié cette cohorte de patients devant être traités par chimiothérapie au cours de la période de 30 jours suivant leur évaluation. Résultats: Nous avons exclu les patients pour lesquels le traitement de chimiothérapie orale ou intraveineuse était déjà en cours ou récemment terminé ou ceux dont le statut s'était amélioré selon l'Έchelle de performance. De la partie restante de la cohorte, 9,3 pourcent (264/2 842) ont reçu le traitement par voie intraveineuse à l'intérieur des 30 jours suivant l'indice de l'Έchelle de performance. Conclusion: Un petit nombre de patients ayant un faible statut ont commencé la traitement de chimiothérapie au cours du mois suivant l'évaluation.

Using the Palliative Performance Scale to Estimate Survival for Patients at the End of Life: A Systematic Review of the Literature

BACKGROUND

The Palliative Performance Scale (PPS) has been widely used for survival prediction among patients with cancer; however, few studies have reviewed PPS scores in heterogeneous palliative care populations across multiple care settings.

OBJECTIVE

The aim of this systematic review was to determine how the PPS tool has been used to estimate survival at the end of life.

METHODS

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed, Embase, and the Cochrane Library were searched for the existing literature published from 2008 to 2017. We synthesized study characteristics, the PPS scores at baseline, and primary outcomes, and explored differences in survival estimates by diagnosis. The quality of the studies was assessed using the Good ReseArch for Comparative Effectiveness (GRACE) checklist.

RESULTS

Seventeen studies were included in this review (nine with cancer and eight with mixed diagnoses). All included studies reported that the PPS exhibited a significant association with survival. Survival estimates ranged from 1 to 3 days for patients with PPS scores of 10% compared with 5 to 36 days for those with scores of 30%. The categorical cut-points for the PPS scores were not consistently reported across studies.

CONCLUSION

This review provides a broad overview on the prognostic value of the PPS tool for survival among multiple patient populations across care settings. Consistent reporting of PPS scores would facilitate the comparison of survival estimates across end-of-life diagnoses.

Predictors of death in an Intensive Care Unit: contribution to the palliative approach

OBJECTIVE

To identify predictors of death in the Intensive Care Unit and relate eligible patients to preferential palliative care.

METHOD

A prospective cohort study that evaluated patients hospitalized for more than 24 hours, subdivided into G1 (patients who died) and G2 (patients who were discharged from hospital). For identifying the predictors for death outcome, the intensivist physician was asked the "surprise question" and clinical-demographic data were collected from the patients. Data were analyzed by descriptive/inferential statistics (p<0.05 significance).

RESULTS

170 patients were evaluated. The negative response to the "surprise question" was related to death outcome. A greater possibility of death (p<0.05) was observed among older and more frail patients with less functionality, chronic cardiac and/or renal insufficiencies or acute non-traumatic neurological insult, with multiorgan failure for more than 5 days, and hospitalized for longer.

CONCLUSION

Predictors of death were related to a subjective evaluation by the physician, the clinical condition of the patient, underlying diseases, the severity of the acute disease and the evolution of the critical illness. It is suggested that patients with two or more predictive criteria receive preferential palliative care.

Distinct Patterns of Conjoint Symptom Distress and Functional Impairment in the Last Year of Life Predict Terminally Ill Cancer Patients' Survival

CONTEXT/OBJECTIVES

Our study addressed important knowledge gaps about trajectories of distinct conjoint symptom-functional states, that is, patterns for different levels of combined symptom distress and functional impairment, over cancer patients' last year and their ability to predict survival.

METHODS

We identified distinct symptom-functional states and explored their changes over 317 terminally ill cancer patients' last year by a transition model using hidden Markov modeling. These distinct symptom-functional states' ability to predict current survival probability, measured in the previous assessment, was evaluated by multivariate Cox regression models.

RESULTS

We identified five worsening, conjoint symptom-functional states: 1) mild symptom distress with high functioning, 2) moderate symptom distress with mild functional impairment, 3) severe symptom distress with moderate functional impairment, 4) moderate symptom distress with severe functional impairment, and 5) profound symptom distress and functional impairment. Trajectories of these five states differed substantially by direction (downward vs. upward) and speed. Participants in States 1-4 had substantially lower risk of subsequent death than those in State 5 (adjusted hazard ratios [95% CI] ranged from 0.048 [0.028-0.081] to 0.434 [0.316-0.579]). The risk of subsequent death differed significantly between patients in any two distinct symptom-functional states, except between those in States 3 and 4.

CONCLUSION

Our identification of five distinct symptom-functional states and their unique transition patterns and prediction of mortality provides all stakeholders with guides for end-of-life care. Goals of end-of-life care should change toward palliative care and effective symptom management for patients with at least moderate symptom distress and substantial functional impairment.

Correlation of Palliative Performance Scale and Survival in Patients With Cancer Receiving Home-Based Palliative Care

The main objective of this study was to examine whether and how the Palliative Performance Scale (PPS), a measure of a patient's function, was predictive of survival time for those in receipt of home-based palliative care. This was a prospective study, which included 194 cancer patients from November 17, 2013, to August 18, 2015. Data were collected from biweekly telephone interviews with caregivers. Kaplan-Meier survival curves were estimated to assess how survival time was correlated with initial PPS scores after admission to the home-based palliative care program. A multivariate extended Cox regression model was used to examine the association between PPS and survival. The results showed that patients with higher PPS scores, that is, better function, had a lower hazard ratio (0.977; 95% confidence interval: 0.965-0.989) and hence longer survival times. The PPS can be used in predicting survival time for home-based palliative care patients.

Evaluation of the symptoms and treatment prescribed to hospitalized patients

OBJECTIVE

Evaluation of the presence of symptoms and suitability in the treatment of patients admitted to medical wards at HU-UFSC. Identification of patients eligible for palliative care (PC).

METHOD

A prospective cohort study, which evaluated patients in the first 48 hours of hospitalization (D1) and after 48 hours (D2). On D1, palliative performance and symptom assessment scales were applied (PPS/ESAS). The treatment established for the control of detected symptoms was also identified. On D2, the ESAS scale was applied again, and the medical prescription reviewed. When the presence of severe symptoms was found, the attending physician was informed. Patients who presented PPS≤60 were eligible for PC prioritization. For statistical analysis Student's t and χ2 tests were used.

RESULTS

168 patients were studied. Of these, 26.8% had PPS≤60. PC was described in one medical chart. Patients with mild symptoms reported significant worsening in the second evaluation, especially worsening in pain (32.3%) and well-being (49.3%). Symptoms considered severe showed significant improvement. There was no control of pain reported as moderate. Prescriptions for pain control were predominantly "if necessary", prevailing the use of non-opioid analgesics and weak opioids. The attending physician was informed of 116 (69%) patients with ESAS score≥4.

CONCLUSION

The control of symptoms, especially those considered mild, was unsatisfactory. Drug prescription was inadequate to control pain, and non-existent for some reported symptoms. There was no adequate prioritization of PC. There is a need for optimization and dissemination of PC among health professionals.

Sequential Assessments of the Eastern Cooperative Oncology Group Performance Scale Enhance Prognostic Value in Patients With Terminally Ill Cancer Receiving Palliative Care

This study aimed to assess the utility of the Eastern Cooperative Oncology Group (ECOG) performance scale assessments on days 1 and 8 of palliative care, as well as scale change between these assessments, as prognostic tools for patients with terminally ill cancer. A total of 2392 patients with terminally ill cancer who received palliative care between January 2006 and December 2011 at a single medical center were analyzed. Our study showed that the ECOG scale is a useful prognostic tool to predict life expectancy in patients with terminally ill cancer. The ECOG scale assessments at different time points under palliative care were independent predictors for overall survival. The combined ECOG scale assessments on days 1 and 8 predicted survival more precisely than using day 1 ECOG scale assessment alone.

Do repeated assessments of performance status improve predictions for risk of death among patients with cancer? A population-based cohort study

BACKGROUND

Prior work has utilized longitudinal information on performance status to demonstrate its association with risk of death among cancer patients; however, no study has assessed whether such longitudinal information improves the predictions for risk of death.

AIM

To examine whether the use of repeated performance status assessments improve predictions for risk of death compared to using only performance status assessment at the time of cancer diagnosis.

DESIGN

This was a population-based longitudinal study of adult outpatients who had a cancer diagnosis and had at least one assessment of performance status. To account for each patient's changing performance status over time, we implemented a Cox model with a time-varying covariate for performance status. This model was compared to a Cox model using only a time-fixed (baseline) covariate for performance status. The regression coefficients of each model were derived based on a randomly selected 60% of patients, and then, the predictive ability of each model was assessed via concordance probabilities when applied to the remaining 40% of patients.

RESULTS

Our study consisted of 15,487 cancer patients with over 53,000 performance status assessments. The utilization of repeated performance status assessments improved predictions for risk of death compared to using only the performance status assessment taken at diagnosis.

CONCLUSION

When studying the hazard of death among patients with cancer, if available, researchers should incorporate changing information on performance status scores, instead of simply baseline information on performance status.

Survival Prediction in Ambulatory Patients With Stage III/IV Non-Small Cell Lung Cancer Using the Palliative Performance Scale, ECOG, and Lung Cancer Symptom Scale

OBJECTIVES

Patients with advanced non-small cell lung cancer (NSCLC) have a life expectancy of less than 1 year. Therefore, it is important to maximize their quality of life and find a tool that can more accurately predict survival.

MATERIALS

The Palliative Performance Scale (PPS) is used to predict survival for patients with advanced disease based on functional dimensions. The value of the PPS in ambulatory patients with cancer has not been examined to date. The Lung Cancer Symptom Scale (LCSS) measures six major symptoms and their effect on symptomatic distress and activity. We evaluated 62 patients with stage III or IV NSCLC and Eastern Cooperative Oncology Group (ECOG) Scale Score ≥1 at baseline in a thoracic oncology clinic. In all, 62 patients had LCSS and PPS evaluated at baseline and 54 patients had 4-week follow-up using LCSS, PPS, and ECOG.

RESULTS

Fifty-four patients completed baseline and follow-up. Mean age was 63.7 years. Sixty-three percent were receiving chemotherapy at evaluation. Seventeen patients died. Mean baseline measures were LCSS 6.18 (1-14); PPS 66.6 (40-90); and ECOG 1.82 (1-4). Censored survival times were calculated from enrollment of the first patient for 380 days. A proportional hazardous model was computed for survival status. Hazard ratios for death were 1.25 (P = .013) for LCSS, 2.12 (P = .027) for ECOG, and 1.02 for PPS (P = .49).

CONCLUSIONS

The LCSS predicted prognosis best in this study. The PPS did not accurately predict prognosis in our patient population.

Repeated assessments of symptom severity improve predictions for risk of death among patients with cancer

CONTEXT

Although prior studies show the importance of self-reported symptom scores as predictors of cancer survival, most are based on scores recorded at a single point in time.

OBJECTIVES

To show that information on repeated assessments of symptom severity improves predictions for risk of death and to use updated symptom information for determining whether worsening of symptom scores is associated with a higher hazard of death.

METHODS

This was a province-based longitudinal study of adult outpatients who had a cancer diagnosis and had assessments of symptom severity. We implemented a time-to-death Cox model with a time-varying covariate for each symptom to account for changing symptom scores over time. This model was compared with that using only a time-fixed (baseline) covariate for each symptom. The regression coefficients of each model were derived based on a randomly selected 60% of patients, and then, the predictive performance of each model was assessed via concordance probabilities when applied to the remaining 40% of patients.

RESULTS

This study had 66,112 patients diagnosed with cancer and more than 310,000 assessments of symptoms. The use of repeated assessments of symptom scores improved predictions for risk of death compared with using only baseline symptom scores. Increased pain and fatigue and reduced appetite were the strongest predictors for death.

CONCLUSION

If available, researchers should consider including changing information on symptom scores, as opposed to only baseline information on symptom scores, when examining hazard of death among patients with cancer. Worsening of pain, fatigue, and appetite may be a flag for impending death.

Combination of initial palliative prognostic index and score change provides a better prognostic value for terminally ill cancer patients: a six-year observational cohort study

CONTEXT

The Palliative Prognostic Index (PPI) is among the most popular scores used to predict life expectancy in terminally ill patients worldwide. PPI assessed on the first day of palliative care might be inappropriate because the contribution from subsequent changes in a patient's condition are not taken into account.

OBJECTIVES

The aim of this study is to determine the utility of sequential PPI assessments as a better prognostic tool for patients with terminal cancer.

METHODS

In total, 2392 terminally ill cancer patients with initial and one-week PPI assessments under the palliative care consultation service between January 2006 and December 2011 at a single medical center in Taiwan were selected. Patients were categorized into initial PPI, Week 1 PPI, score change (initial PPI - Week 1 PPI; Δscore), and combined initial PPI and Δscore subgroups for survival analysis.

RESULTS

Overall median survival was 32 days (range eight to 180 days), and 2183 patients (91.3%) died within 180 days of palliative care consultation service care. A significant difference in survival was observed among patient subgroups (P < 0.001). Subgroup survival analysis showed significant difference in patients with Δscores >0, 0, and <0 in each prognostic group categorized by initial PPI. The c-statistic for predicting life expectancy <30 days was significantly higher with the combined initial PPI and Δscore (c-statistic, 0.71; 95% CI, 0.694-0.731) than with the initial PPI (c-statistic, 0.63; 95% CI, 0.61-0.65), Week 1 PPI (c-statistic, 0.67; 95% CI, 0.652-0.690), or Δscore (c-statistic, 0.64; 95% CI, 0.62-0.66).

CONCLUSION

Combination of initial PPI and score change is more useful than initial PPI for identifying patients with poor outcomes in good prognostic groups and patients with better outcomes in poor prognostic groups.

Palliative performance scale and survival among outpatients with advanced cancer

PURPOSE

Previous studies have examined the association between the Palliative Performance Scale (PPS) and survival duration; however, few have examined patients with incurable cancer in the outpatient setting. In addition to exploring this association further, the purpose of this study was to identify key PPS markers that could serve as triggers to signify the need for key care discussions.

METHODS

Study subjects were followed prospectively from the time of referral for a specialist palliative care consultation until death. PPS ratings and survival estimates were determined for each visit.

RESULTS

For the final study population of 368 patients, at baseline, the median PPS rating was 60. Overall median and mean survival duration were approximately 4 and 6 months, respectively. Median survival duration for patients with PPS ratings of 70, 60, and 50 were found to be approximately 6, 3, and 2 months, respectively. Twenty-four percent of all survival estimates were found to be accurate.

CONCLUSIONS

Given the ongoing challenge of inaccurate survival estimates, this data suggests what may be of greatest clinical utility is to use specific PPS ratings as triggers for key care discussions among patients with incurable and progressive cancer.

Magnitude of score change for the palliative prognostic index for survival prediction in patients with poor prognostic terminal cancer

PURPOSE

The use of the palliative prognostic index (PPI) when used only at an initial assessment might be inappropriate as a prognostic tool because it does not reflect the patient's clinical course. The purpose of this study was to assess the utility of PPI score change (∆score) between two assessments as a prognostic tool in terminally ill cancer patients categorized as having a poor prognosis.

METHODS

A total of 1,035 terminally ill cancer patients categorized as having a poor prognosis (initial PPI score >6) under palliative care between January 2006 and December 2011 at a single medical center in Taiwan were selected. Patients were categorized by magnitude of ∆score between the initial PPI and week 1 PPI assessments into five groups (<-20, -20 to 0, 0, 0 to 20, and >20 %) for survival analysis.

RESULTS

The median survival was 22 days (range, 8-180 days) in all patients. Median survival duration was 78, 32, 23, 17, and 14 days, and the death rate at the study end was 78.9, 87.1, 96.2, 100, and 100 % in each group, respectively. The c-statistic value for predicting life expectancy less than 30, 60, and 90 days was significantly higher with magnitude of ∆score than with the initial PPI score (p < 0.05).

CONCLUSIONS

Magnitude of PPI score change within 1-week interval provides a significant difference in survival prediction and is more reliable than initial PPI alone to identify terminally ill cancer patients with better outcome potential in those patients considered to have a poor prognosis.

EORTC QLQ-C15-PAL quality of life score as a prognostic indicator of survival in patients with far advanced cancer

PURPOSE

Quality of life (QoL) and performance status predict survival in advanced cancer patients; these relationships have not been explored in the hospice palliative care setting. The aim of this study was to examine the survival predictability of patient-reported QoL using the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C15-PAL questionnaire in far advanced cancer inpatients at the very end of life.

METHODS

This is a retrospective cohort study. Patients reported QoL using the EORTC QLQ-C15-PAL. One hundred sixty-two inpatients in hospice palliative wards of six hospitals in South Korea were followed until death or the end of the study. Additional symptoms and performance status were assessed by the MD Anderson Symptom Inventory-Korean (MDASI-K), Palliative Performance Scale (PPS) and Eastern Cooperative Oncology Group (ECOG) performance status. Correlations between EORTC QLQ-C15-PAL, MDASI-K, PPS, and ECOG were assessed. Survival analyses were performed using Cox proportional hazard models.

RESULTS

Patients' median survival was less than 1 month. Physician-reported PPS significantly predicted survival (hazard ratio [HR] 0.493; p<0.001). From the EORTC QLQ-C15-PAL, patient-reported physical functioning predicted survival (HR=0.65; p<0.001). Other six domains of EORTC QLQ-C15-PAL were significantly related to survival after adjustment. Those domains were global health status, emotional functioning, fatigue, nausea/vomiting, appetite loss, and constipation.

CONCLUSIONS

EORTC QLQ-C15-PAL can be an independent prognostic factor in inpatients with far advanced cancer. Patient-reported physical functioning showed survival predictability as good as physician-reported performance status. It is notable that the QLQ instrument is useful even for patients in their final month of life. Cancer anorexia-cachexia syndrome-related symptoms may be independent prognostic symptoms. Prospective study is warranted.

A Markov multistate analysis of the relationship between performance status and death among an ambulatory population of cancer patients

BACKGROUND

The relationship between performance status and death among cancer patients has been of increasing interest over the past years. However, few studies have implemented statistical models that adequately capture the longitudinal nature of performance status assessments collected under intermittent observation.

AIM

The main research aims were to examine the association between performance status and death and to determine the probability of deterioration in performance status over time.

DESIGN

This was a population-based longitudinal study among adult outpatients diagnosed with cancer. Throughout their observation period, all patients were repeatedly assessed for performance status using an 11-point scale with a score of 100 being the best, 10 being the worst and 0 representing death. A Markov multistate model accounting for intermittent observation was implemented in which each score represented a distinct state in the model.

RESULTS

The cohort consisted of 27,739 patients with over 157,000 assessments. The rate of transition to death increases with a quadratic trend as performance status declines. The 1-month and 3-month probability of deterioration also increases with a quadratic trend as performance status declines. The relative rate of transition to death decreases as we compare lower scores (relative rate = 2.20 for comparing scores 90 vs 100 and relative rate = 1.23 for comparing scores 10 vs 20).

CONCLUSION

There is a significant relationship between performance status and rate of transition to death. The Markov multistate model provides a comprehensive understanding of the shape of this relationship, which facilitates the interpretation of performance status and provides strength in its use as a prognostic tool in a clinical setting.