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

Reliability and validity of the Arabic translation of the palliative performance scale

OBJECTIVE

The aim of this study was to translate the Palliative Performance Scale (PPSv2) into Arabic and to test the reliability and validity of the PPS Arabic translation (PPS-Arabic).

METHOD

The PPSv2 was translated into Modern Standard Arabic using a forward-backward method. Inter-rater and intra-rater reliabilities were tested in a pilot study that included 20 patients. The validation study included 150 cancer patients. Patients were divided according to their treatment plan into three groups (in-remission, palliative chemotherapy, and best supportive care) to perform hypothesis-testing construct validity. Validity was further evaluated by correlating PPS-Arabic with the Karnofsky Performance Scale (KPS), the Eastern Cooperative Oncology Group (ECOG) scale, and Physical Functioning (PF2) and Role Functioning (RF2) scales of the European Organization for Research and Treatment of Cancer quality of life questionnaire (EORTC QLQ-C30).

RESULTS

The intraclass correlation coefficients for the intra-rater and inter-rater reliability were 0.935 (95% CI: 0.88-0.965; p < 0.001) and 0.965 (95% CI: 0.934-0.981; p < 0.001), respectively. The PPS-Arabic internal consistency Cronbach's alpha was 0.986. The average PPS-Arabic score differed significantly (p < 0.001) between the three groups of patients being 89 for in-remission, 58 for palliative chemotherapy, and 38 for best supportive care. The PPS-Arabic score correlated significantly (p < 0.001) with the KPS, ECOG performance scale, and the EORTC QLQ-C30 PF2 and RF2 scales.

CONCLUSION

The PPS-Arabic is a reliable and valid tool for the assessment of performance status of cancer patients.

Factors determining ultra-short-term survival and the commencement of active treatment in high-grade serous ovarian cancer: a case comparison study

Background

Despite improvements in median survival some patients with advanced ovarian cancer die within 100 days of diagnosis; the reasons for which remain poorly understood.

Here we investigate if ultra short-term survival can be explained by patient characteristics or treatment pathways.

Methods

A nested case comparison study was used to examine differences between patients with high grade serous ovarian/fallopian tube cancer who died within 100 days (n = 28) compared to a comparison group of patients matched for histology and including any survival greater than 100 days (n = 134).

Results

Cases and comparison patients had similar ages, BMI, ACE-27, deprivation indices, and distribution of disease on CT. There were no significant delays in time to diagnosis or treatment (p = 0.68) between the groups.

However, cases had lower serum albumin, haemoglobin and higher platelet counts than matched comparison patients (p < 0.0001) and a worse performance score (P = 0.006).

Conclusion

Patients who die rapidly after a diagnosis of ovarian cancer are only slightly older and have similar pre treatment frailty compared to patients whose survival approaches the median. However they do appear to undergo greater physiological compromise as a result of their disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08019-9.

Toward Modernization of Geriatric Oncology by Digital Health Technologies

The number of older adults with cancer is increasing. Over the past 3 decades, geriatric oncology research has focused on improving the assessment of frailty and fitness of older adults with cancer as well as methods of improving their outcomes. At the same time, advances in digital health technologies have opened new frontiers for reaching this goal. Digital health technologies encompass a variety of solutions, from electronic patient-reported outcomes (ePROs) to Big Data and wireless sensors. These solutions have the potential to further advance our understanding of patients' experiences during cancer treatment. Whereas the data on the feasibility and utility of such solutions in the care of older adults with cancer are limited, interest from digital health oncology researchers to further explore the benefits of these products is increasing. In this article, we describe the focus of geriatric oncology, the rationale behind the need to explore digital health technologies in this setting, and emerging data and ongoing studies, as well as provide guidelines for proper selection, implementation, and testing of digital health solutions in the context of geriatric oncology.

Development and Validation of a Prognostic Survival Model With Patient-Reported Outcomes for Patients With Cancer

IMPORTANCE

Existing prognostic cancer tools include biological and laboratory variables. However, patients often do not know this information, preventing them from using the tools and understanding their prognosis.

OBJECTIVE

To develop and validate a prognostic survival model for all cancer types that incorporates information on symptoms and performance status over time.

DESIGN, SETTING, AND PARTICIPANTS

This is a retrospective, population-based, prognostic study of data from patients diagnosed with cancer from January 1, 2008, to December 31, 2015, in Ontario, Canada. Patients were randomly selected for model derivation (60%) and validation (40%). The derivation cohort was used to develop a multivariable Cox proportional hazards regression model with baseline characteristics under a backward stepwise variable selection process to predict the risk of mortality as a function of time. Covariates included demographic characteristics, clinical information, symptoms and performance status, and health care use. Model performance was assessed on the validation cohort by C statistics and calibration plots. Data analysis was performed from February 6, 2018, to November 6, 2019.

MAIN OUTCOMES AND MEASURES

Time to death from diagnosis (year 0) recalculated at each of 4 annual survivor marks after diagnosis (up to year 4).

RESULTS

A total of 255 494 patients diagnosed with cancer were identified (135 699 [53.1%] female; median age, 65 years [interquartile range, 55-73 years]). The cohort decreased to 217 055, 184 822, 143 649, and 109 569 patients for each of the 4 years after diagnosis. In the derivation cohort year 0, and the most common cancers were breast (30 855 [20.1%]), lung (19 111 [12.5%]), and prostate (18 404 [12.0%]). A total of 47 614 (31.1%) had stage III or IV disease. The mean (SD) time to death in year 0 was 567 (715) days. After backward stepwise selection in year 0, the following factors were associated with increased risk of death by more than 10%: being hospitalized; having congestive heart failure, chronic obstructive pulmonary disease, or dementia; having moderate to high pain; having worse well-being; having functional status in the transitional or end-of-life phase; having any problems with appetite; receiving end-of-life home care; and living in a nursing home. Model discrimination was high for all models (C statistic: 0.902 [year 0], 0.912 [year 1], 0.912 [year 2], 0.909 [year 3], and 0.908 [year 4]).

CONCLUSIONS AND RELEVANCE

The model accurately predicted changing cancer survival risk over time using clinical, symptom, and performance status data and appears to have the potential to be a useful prognostic tool that can be completed by patients. This knowledge may support earlier integration of palliative care.

Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods

BACKGROUND

Clinical prediction models (CPMs) predict the risk of health outcomes for individual patients. The majority of existing CPMs only harness cross-sectional patient information. Incorporating repeated measurements, such as those stored in electronic health records, into CPMs may provide an opportunity to enhance their performance. However, the number and complexity of methodological approaches available could make it difficult for researchers to explore this opportunity. Our objective was to review the literature and summarise existing approaches for harnessing repeated measurements of predictor variables in CPMs, primarily to make this field more accessible for applied researchers.

METHODS

MEDLINE, Embase and Web of Science were searched for articles reporting the development of a multivariable CPM for individual-level prediction of future binary or time-to-event outcomes and modelling repeated measurements of at least one predictor. Information was extracted on the following: the methodology used, its specific aim, reported advantages and limitations, and software available to apply the method.

RESULTS

The search revealed 217 relevant articles. Seven methodological frameworks were identified: time-dependent covariate modelling, generalised estimating equations, landmark analysis, two-stage modelling, joint-modelling, trajectory classification and machine learning. Each of these frameworks satisfies at least one of three aims: to better represent the predictor-outcome relationship over time, to infer a covariate value at a pre-specified time and to account for the effect of covariate change.

CONCLUSIONS

The applicability of identified methods depends on the motivation for including longitudinal information and the method's compatibility with the clinical context and available patient data, for both model development and risk estimation in practice.

The Spanish Adaptation of the Palliative Performance Scale (Version 2) Among Cancer Patients at the End of Life: Psychometric Properties

BACKGROUND

Palliative Performance Scale (PPS) is a reliable tool to assess performance status in cancer patients receiving palliative care (PC). Spanish validated and culturally adapted tools are needed.

OBJECTIVES

The objectives are to develop PPS translation and cross-cultural adaptation into Spanish and to assess its psychometric properties.

DESIGN

Translation process with cross-cultural adaptation to produce Spanish Palliative Performance Scale (PPS-SPANISH).

SETTINGS

PC Team at one University hospital in Spain.

PARTICIPANTS

Fifteen advanced cancer patients (60 assessments) were included for PPS translation and validation and 250 patients for cross-sectional analysis. All participants were recruited at oncology ward, emergency area, and outpatient clinic by PC team professionals. Informed consent was given. Average age was 66.4 ± 13 years (60% men).

METHODS

The process is designed in three steps. In Step 1, PPS translation and reverse translation into Spanish (three bilingual speakers) and linguistic complexity measurement were performed. In Step 2, readability and intelligibility assessment was carried out. In Step 3, a pilot study was conducted to assess test-retest reliability followed by a cross-sectional study to measure internal consistency. Inclusion criteria were the same for two samples. Demographic data were also analyzed by descriptive statistics.

RESULTS

Following cultural, linguistic, and grammatical adaptation, PPS-SPANISH was readable and reliable. The analysis of the test-retest reliability after 48 hours showed intraclass correlations >0.60. Cronbach's alpha coefficient was 0.99 (0.988-0.992). There was high agreement with other functional assessment tools (Barthel Index and Karnofsky Performance Status Index).

CONCLUSIONS

PPS-SPANISH showed reliability and validity, and it is suitable to assess performance status in cancer patients receiving PC.

Prevalence of Sudden Death in Palliative Care: Data From the Australian Palliative Care Outcomes Collaboration

CONTEXT

Advanced, life-limiting illnesses are likely to have a predictable functional decline through a terminal phase to death, but some patients may also die suddenly. To date, empirical evidence characterizing "sudden death" in hospice/palliative care is lacking.

OBJECTIVES

The aim of this study was to determine prevalence and clinicodemographic predictors of sudden death in hospice/palliative care.

METHODS

This is a longitudinal consecutive cohort study of prospectively collected national data in 104 specialist palliative care services from the Australian Palliative Care Outcomes Collaboration. Patients who died between July 1, 2013, and June 30, 2014, with one or more measurement of Australian-modified Karnofsky Performance Status (AKPS) in the last 30 days of life were included. "Sudden death" was defined as a lowest AKPS score of 50 or more in the last seven days of life and excluded anyone with "terminal phase" as their last phase before death. Predictors were defined using logistic regression.

RESULTS

In total, 13,966 patients were included, mean age 73.6 (SD 13.6) years, 46% women, and 77% had cancer. During the seven days before death, there were 20,992 AKPS measurements; median 1 (interquartile range 1-2) per patient. Four percent of deaths (one of 25) were sudden, predicted independently by having lung cancer (odds ratio [OR] 2.64), cardiovascular disease (OR 1.94), other cancers (OR 1.63), being male (OR 1.23), younger, worse fatigue, and worse breathlessness. Sudden death was associated with higher rates of death at home (OR 3.2; 95% CI 2.9 to 3.6).

CONCLUSION

This study quantifies rates of sudden death in hospice/palliative care and has implications for conversations about prognosis between clinicians, patients, and their families.

Prognostic factors in patients with malignant pleural effusion: Is it possible to predict mortality in patients with good performance status?

BACKGROUND AND OBJECTIVES

The aim of this study was to identify predictors of mortality only in patients with malignant pleural effusion (MPE) showing good performance status which required pleural palliative procedures.

METHODS

All patients with MPE submitted to pleural palliative procedure were enrolled in a prospective study between 2013 and 2014. Patients with Eastern cooperative oncology group (ECOG) score zero, one, and two were considered with good performance status. The possible prognostic factors were tested for significance using the log-rank test (Kaplan-Meier method) and those with significance on univariate analysis were entered into a multivariable Cox model.

RESULTS

A total of 64 patients were included in the analysis. Median follow-up time for surviving patients was 263 days. Median survival for the entire cohort was not reached yet. In the multivariate analysis, gastrointestinal primary site (P = 0.006), low albumin concentration in the pleural fluid (P = 0.017), and high serum NLR (P = 0.007) were associated with mortality.

CONCLUSION

In our cohort of ECOG 0-2 patients with MPE submitted to pleural palliative procedures, gastrointestinal malignancy compared to other sites, low pleural fluid albumin and high NLR were significantly associated with mortality. The identification of these prognostic factors may assist the choice of the optimal palliative technique. J. Surg. Oncol. 2016;113:570-574. © 2016 Wiley Periodicals, Inc.