scholarly journals CA-PROM: Validation of a general patient-reported outcomes measure for Chinese patients with cancer

2020 ◽  
Vol 67 ◽  
pp. 101774
Author(s):  
Xiaojuan Hu ◽  
Zhiqiang Zhao ◽  
Shao-Kai Zhang ◽  
Yanhong Luo ◽  
Hongmei Yu ◽  
...  
Keyword(s):  
Patient Reported Outcomes ◽  
Chinese Patients ◽  
Patients With Cancer ◽  
Patient Reported

scholarly journals The role of EORTC QLQ-C15-PAL scores and inflammatory biomarkers in predicting survival in terminally ill patients with cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nanako Koyama ◽  
Chikako Matsumura ◽  
Yoshihiro Shitashimizu ◽  
Morito Sako ◽  
Hideo Kurosawa ◽  
...  
Keyword(s):  
Patient Reported Outcomes ◽  
Cox Regression ◽  
Terminally Ill ◽  
Inflammatory Biomarkers ◽  
Survival Curves ◽  
Patients With Cancer ◽  
Terminally Ill Patients ◽  
Patient Reported ◽  
Eortc Qlq

Abstract Background The clinical use of patient-reported outcomes as compared to inflammatory biomarkers for predicting cancer survival remains a challenge in palliative care settings. We evaluated the role of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative scores (EORTC QLQ-C15-PAL) and the inflammatory biomarkers C-reactive protein (CRP), albumin (Alb), and neutrophil-lymphocyte ratio (NLR) for survival prediction in patients with advanced cancer. Methods This was an observational study in terminally ill patients with cancer hospitalized in a palliative care unit between June 2018 and December 2019. Patients’ data collected at the time of hospitalization were analyzed. Cox regression was performed to examine significant factors influencing survival. A receiver operating characteristic (ROC) analysis was performed to estimate cut-off values for predicting survival within 3 weeks, and a log-rank test was performed to compare survival curves between groups divided by the cut-off values. Results Totally, 130 patients participated in the study. Cox regression suggested that the QLQ-C15-PAL dyspnea and fatigue scores and levels of CRP, Alb, and NLR were significantly associated with survival time, and cut-off values were 66.67, 66.67, 3.0 mg/dL, 2.5 g/dL, and 8.2, respectively. The areas under ROC curves of these variables were 0.6–0.7. There were statistically significant differences in the survival curves between groups categorized using each of these cut-off values (p < .05 for all cases). Conclusion Our findings suggest that the assessment of not only objective indicators for the systemic inflammatory response but also patient-reported outcomes using EORTC QLQ-C15-PAL is beneficial for the prediction of short-term survival in terminally ill patients with cancer.

scholarly journals Web-Based Patient-Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care): Multicenter Pragmatic Nonrandomized Trial

10.2196/19685 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e19685
Author(s):  
Afaf Girgis ◽  
Ivana Durcinoska ◽  
Anthony Arnold ◽  
Joseph Descallar ◽  
Nasreen Kaadan ◽  
...  
Keyword(s):  
Emergency Department ◽  
Patient Reported Outcomes ◽  
Well Being ◽  
Patient Reported Outcome Measures ◽  
Patient Reported Outcome ◽  
Self Management ◽  
Diverse Population ◽  
Web Based ◽  
Patients With Cancer ◽  
Patient Reported

Background Despite the acceptability and efficacy of e–patient-reported outcome (ePRO) systems, implementation in routine clinical care remains challenging. Objective This pragmatic trial implemented the PROMPT-Care (Patient Reported Outcome Measures for Personalized Treatment and Care) web-based system into existing clinical workflows and evaluated its effectiveness among a diverse population of patients with cancer. Methods Adult patients with solid tumors receiving active treatment or follow-up care in four cancer centers were enrolled. The PROMPT-Care intervention supported patient management through (1) monthly off-site electronic PRO physical symptom and psychosocial well-being assessments, (2) automated electronic clinical alerts notifying the care team of unresolved clinical issues following two consecutive assessments, and (3) tailored online patient self-management resources. Propensity score matching was used to match controls with intervention patients in a 4:1 ratio for patient age, sex, and treatment status. The primary outcome was a reduction in emergency department presentations. Secondary outcomes were time spent on chemotherapy and the number of allied health service referrals. Results From April 2016 to October 2018, 328 patients from four public hospitals received the intervention. Matched controls (n=1312) comprised the general population of patients with cancer, seen at the participating hospitals during the study period. Emergency department visits were significantly reduced by 33% (P=.02) among patients receiving the intervention compared with patients in the matched controls. No significant associations were found in allied health referrals or time to end of chemotherapy. At baseline, the most common patient reported outcomes (above-threshold) were fatigue (39%), tiredness (38.4%), worry (32.9%), general wellbeing (32.9%), and sleep (24.1%), aligning with the most frequently accessed self-management domain pages of physical well-being (36%) and emotional well-being (23%). The majority of clinical feedback reports were reviewed by nursing staff (729/893, 82%), largely in response to the automated clinical alerts (n=877). Conclusions Algorithm-supported web-based systems utilizing patient reported outcomes in clinical practice reduced emergency department presentations among a diverse population of patients with cancer. This study also highlighted the importance of (1) automated triggers for reviewing above-threshold results in patient reports, rather than passive manual review of patient records; (2) the instrumental role nurses play in managing alerts; and (3) providing patients with resources to support guided self-management, where appropriate. Together, these factors will inform the integration of web-based PRO systems into future models of routine cancer care. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12616000615482; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370633 International Registered Report Identifier (IRRID) RR2-10.1186/s12885-018-4729-3

scholarly journals Clinical and patient‐reported outcomes of Chinese patients undergoing haemodialysis in hospital or in the community: A 1‐year longitudinal study

Nephrology ◽  
2016 ◽  
Vol 21 (7) ◽  
pp. 617-623 ◽  
Author(s):  
Julie Y Chen ◽  
Eric YF Wan ◽  
Edmond PH Choi ◽  
Carlos KH Wong ◽  
Anca KC Chan ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Patient Reported Outcomes ◽  
Chinese Patients ◽  
Patient Reported

scholarly journals Implementing a Method for Evaluating Patient-Reported Outcomes Associated With Oral Oncolytic Therapy

2017 ◽  
Vol 13 (4) ◽  
pp. e395-e400 ◽  
Author(s):  
Emily Mackler ◽  
Laura Petersen ◽  
Jane Severson ◽  
Douglas W. Blayney ◽  
Lydia L. Benitez ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Patient Reported Outcomes ◽  
Assessment Tool ◽  
Symptom Burden ◽  
Oncolytic Therapy ◽  
Patients With Cancer ◽  
Patient Reported ◽  
Edmonton Symptom Assessment Scale ◽  
Oral Oncolytics

Introduction: The paradigm shift in health care toward value-based reimbursement has brought emphasis to providing better quality of care to patients with chronic diseases, including patients with cancer. In accordance with providing better quality of care to patients, there has been a growing interest in evaluating quality of life through patient-reported outcomes (PROs). The revised Edmonton Symptom Assessment Scale (ESAS-r) is a tool that can be used to assess PROs and has been validated for use in patients with cancer. This initiative sought to use this standard assessment tool to acquire PROs concerning symptom burden from patients prescribed oral oncolytics. Patients and Methods: Eight oncology practices in the state of Michigan used a modified ESAS-r to evaluate symptom burden of patients prescribed oral oncolytics before each outpatient visit. Thirteen symptoms were categorized as mild (0 to 3), moderate (4 to 6), or severe (7 to 10). Results: A total of 1,235 modified ESAS-r surveys were collected and analyzed; 82.5% of symptoms were categorized as mild, 11.9% of symptoms were categorized as moderate, and 5.6% of symptoms were categorized as severe. Conclusion: PROs can be evaluated through the use of a standardized tool, such as the ESAS-r, in oncology patients receiving oral oncolytic therapy. Implementing such a tool in both community and academic practices is feasible and may facilitate improvements in the quality of care.

scholarly journals GC-PROM: validation of a patient-reported outcomes measure for Chinese patients with gastric cancer

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Xiaojuan Hu ◽  
Fen Zhao ◽  
Hongmei Yu ◽  
Yanhong Luo ◽  
Jinchun Liu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Patient Reported Outcomes ◽  
Chinese Patients ◽  
Patient Reported

Augmenting machine learning algorithms to predict mortality using patient-reported outcomes in oncology.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1510-1510
Author(s):  
Ravi Bharat Parikh ◽  
Jill Schnall ◽  
Manqing Liu ◽  
Peter Edward Gabriel ◽  
Corey Chivers ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Machine Learning ◽  
Mortality Risk ◽  
Patient Reported Outcomes ◽  
Machine Learning Algorithms ◽  
Measurement Information ◽  
Patients With Cancer ◽  
Patient Reported ◽  
Mortality Table

1510 Background: Machine learning (ML) algorithms based on electronic health record (EHR) data have been shown to accurately predict mortality risk among patients with cancer, with areas under the curve (AUC) generally greater than 0.80. While patient-reported outcomes (PROs) may also predict mortality among patients with cancer, it is unclear whether routinely-collected PROs improve the predictive performance of EHR-based ML algorithms. Methods: This cohort study included 8600 patients with cancer who had an outpatient encounter at one of 18 medical oncology practices in a large academic health system between July 1st, 2019 and January 1st, 2020. 4692 (54.9%) patients completed assessments of symptoms, performance status, and quality of life from the PRO version of the Common Terminology Criteria for Adverse Events and the Patient-Reported Outcomes Measurement Information System Global v.1.2 scales. We hypothesized that ML models predicting 180-day all-cause mortality based on EHR + PRO data would improve AUC compared to ML models based on EHR data alone. We assessed univariate and adjusted associations between each PRO and 180-day mortality. To train the EHR-only model, we fit a Least Absolute Shrinkage and Selection Operator (LASSO) regression using 192 EHR demographic, comorbidity, and laboratory variables. To train the EHR + PRO model, we used a two-phase approach to fit a model using EHR data for all patients and PRO data for those who completed assessments. To test our hypothesis, we compared the bootstrapped AUC, area under the precision-recall curve (AUPRC), and sensitivity at a 20% risk threshold for both models. Results: 464 (5.4%) patients died within 180 days of the encounter. Decreased quality of life, functional status, and appetite were associated with greater 180-day mortality (Table). Compared to the EHR-only model, the EHR + PRO model significantly improved AUC (0.86 [95% CI 0.85-0.86] vs. 0.80 [95% CI 0.80-0.81]), AUPRC (0.40 [95% CI 0.37-0.42] vs. 0.30 [95% CI 0.28-0.32]), and sensitivity (0.45 [95% CI 0.42-0.48] vs. 0.33 [95% CI 0.30-0.35]). Conclusions: Routinely collected PROs augment EHR-based ML mortality risk algorithms. ML algorithms based on EHR and PRO data may facilitate earlier supportive care for patients with cancer. Association of PROs with 180-day mortality.[Table: see text]

scholarly journals Using patient reported outcomes in oncology clinical practice

2016 ◽  
Vol 13 (1) ◽  
pp. 6-11 ◽  
Author(s):  
Sarah A. Kelleher ◽  
Tamara J. Somers ◽  
Tracie Locklear ◽  
Alexandra D. Crosswell ◽  
Amy P. Abernethy
Keyword(s):  
Symptom Severity ◽  
Psychosocial Functioning ◽  
Self Efficacy ◽  
Symptom Management ◽  
Patient Reported Outcomes ◽  
Tablet Computer ◽  
Cancer Type ◽  
Pain Symptom ◽  
Patients With Cancer ◽  
Patient Reported

AbstractBackground and aimsPatient reported outcomes (PROs) are increasingly being implemented into the care of patients with cancer. The use of a standard set of PROs (e.g., pain) in cancer is becoming established and there is interest in what additional PROs might provide valuable information. The goal of this observational study was to examine how the PROs of self-efficacy for pain and other symptoms assessed at the point of service were associated with pain, symptom severity and distress, and physical and psychosocial functioning in a sample of breast and gastrointestinal patients. We also sought to examine differences in these relationships by cancer type (breast and gastrointestinal) as well as understand differences in self-assessment mode (paper/pencil or electronic tablet).Methods178 patients with breast (n = 65) and gastrointestinal cancer (n = 113) completed the Chronic Pain Self Efficacy Scale, M.D. Anderson Symptom Inventory, and Functional Assessment of Cancer Therapy – General questionnaires. Measures were completed with paper and pencil and electronically using a tablet computer while patients waited for their clinical appointment. Responses from the initial completed questionnaires on both the paper and electronic instruments were analyzed.ResultsPatients’ self-efficacy scores for pain and other symptoms correlated positively with pain, symptom severity and distress, and physical and psychosocial functioning; patients with lower levels of self-efficacy reported poorer outcomes and functioning overall. The results were independent of cancer type and mode of assessment. No statistically significant differences were found in the PROs when collected by electronic technology versus paper-pencil mode; patients were very satisfied with using the tablet computer to complete the PRO measures.Conclusions and implicationsOur results suggest that self-efficacy for pain and symptom management may be a beneficial addition to clinic-based PRO assessment batteries for patients with cancer and other chronic diseases. Existing short, validated symptom self-efficacy scales could easily be integrated into clinical practice to help healthcare providers identify patients that might benefit from intervention. Study results also support existing research that suggests electronic approaches are a practical way to collect PRO data, including self-efficacy data, in the clinic. Overall, our data suggest that patients who have particularly low levels of self-efficacy for pain and symptom management may be at risk for higher levels of pain and disability. Thus, if self-efficacy for pain and symptom management were routinely collected at the time of clinical service, psychosocial interventions to improve self-efficacy for pain and symptom management, and in turn overall quality of life, could be implemented in a timely fashion.

scholarly journals The Role of EORTC QLQ-C15-PAL Scores and Inflammatory Biomarkers in Predicting Survival in Terminally Ill Patients with Cancer

2020 ◽  
Author(s):  
Nanako Koyama ◽  
Chikako Matsumura ◽  
Yoshihiro Shitashimizu ◽  
Morito Sako ◽  
Hideo Kurosawa ◽  
...  
Keyword(s):  
Palliative Care ◽  
Patient Reported Outcomes ◽  
Cox Regression ◽  
Terminally Ill ◽  
Inflammatory Biomarkers ◽  
Survival Curves ◽  
Patients With Cancer ◽  
Terminally Ill Patients ◽  
Patient Reported ◽  
Eortc Qlq

Abstract Background The clinical use of patient-reported outcomes as compared to inflammatory biomarkers for predicting cancer survival remains a challenge in palliative care settings. We evaluated the accuracy of survival prediction in both indicators of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 15 Palliative scores (EORTC QLQ-C15-PAL) and the inflammatory biomarkers C-reactive protein (CRP), albumin (Alb), and neutrophil-lymphocyte ratio (NLR) in patients with advanced cancer. Methods This was an observational study in terminally ill patients with cancer hospitalized in a palliative care unit between June 2018 and December 2019. Patients’ data collected at the time of hospitalization were analyzed. Cox regression was performed to examine significant factors influencing survival. A receiver operating characteristic (ROC) analysis was performed to estimate cut-off values for predicting survival within 3 weeks, and a log-rank test was performed to compare survival curves between groups divided by the cut-off values. Results Totally, 130 patients participated in the study. Cox regression suggested that the QLQ-C15-PAL dyspnea and fatigue scores and levels of CRP, Alb, and NLR were significantly associated with survival time, and cut-off values were 66.67, 66.67, 3.0 mg/dL, 2.5 g/dL, and 8.2, respectively. The areas under ROC curves of these variables were 0.6–0.7. There were statistically significant differences in the survival curves between groups categorized using each of these cut-off values (p < .05 for all cases). Conclusion Our findings suggest that the assessment of not only objective indicators for the systemic inflammatory response but also patient-reported outcomes using EORTC QLQ-C15-PAL is beneficial for the prediction of short-term survival in terminally ill patients with cancer.

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