Validating a Patient-Reported Outcomes-Derived Algorithm for Classifying Symptom Complexity Levels Among Patients With Cancer

Long-term outcomes and associated factors among intensive care unit survivors in a low-income country: a multicenter prospective cohort study

OBJECTIVE

Post-ICU survivors face higher mortality and often require costly rehabilitation or palliative care, such as occupational therapy, physiotherapy and hospice. However, there is a lack of data quantifying the demand for these services, particularly in developing countries like Uganda. Therefore, this prospective cohort study aimed to investigate the 90-day mortality rate, functional status, and mortality risk factors among 121 ICU patients discharged from three tertiary hospital ICUs in Uganda by tracking their vital and physical functional status for three months with follow-ups on days 30, 60, and 90, and identifying risk factors through Cox regression.

RESULTS

The study revealed that 18 out of 121 ICU patients (14.88%, 95% CI: 9.52-22.51%) died within 90 days post-discharge, while 36.36% achieved normal physical functional status. Factors associated with higher 90-day mortality included raised intracranial pressure (HR 1.92, 95% CI: 1.76-2.79, p = 0.04), acute kidney injury (HR 4.13, 95% CI: 2.16-7.89, p < 0.01), and renal replacement therapy (HR 3.34, 95% CI: 2.21-5.06, p < 0.01). The high mortality rate and the fact that nearly two-thirds of patients did not attain normal functional status 90 days post discharge underscores the need for enhanced post-ICU rehabilitation services.

Designing and Validating a Comprehensive Patient-Reported Outcomes Measure for Ambulatory Cancer Settings: The Revised Edmonton Symptom Assessment System for Cancer

PURPOSE

Patient-reported outcomes (PROs) information has been routinely collected in Cancer Care Alberta (CCA) for years using the revised Edmonton Symptom Assessment System (ESAS-r) and Canadian Problem Checklist (CPC). There was interest in combining these into a more comprehensive single measure tailored to ambulatory cancer settings. The purpose of this study was to validate an expanded and redesigned ESAS-r called the ESAS-r Cancer.

METHODS

Stakeholder engagement, a review of the literature, and 2 years of CPC data collected in the cancer program informed the addition of six symptoms to the ESAS-r. To assess and validate the measure, 1,600 randomly sampled patients were mailed paper copies of the ESAS-r Cancer, ESAS-r, and a validated, comprehensive PRO measure called the Memorial System Assessment Scale-Short Form (MSAS-SF), which is often used with patients with cancer. Canonical Correlation Analysis and exploratory factor analyses were performed to assess concurrent and construct validity of the ESAS-r Cancer against ESAS-r, using MSAS-SF as the reference measure for comparison. Cronbach α was calculated to assess reliability.

RESULTS

Four hundred and sixty-one patients (29% response rate) completed all three questionnaires. ESAS-r Cancer showed higher numerical correlation than ESAS-r and accounted for more information included on MSAS-SF, explaining slightly more variance than ESAS-r (75.2% v 73.5%). The three-dimensional factor structure of ESAS-r Cancer outperformed the two-dimensional factor structure of ESAS-r. The reliability of ESAS-r Cancer was verified and found to be slightly higher than ESAS-r (Cronbach α = .903 v .884).

CONCLUSION

ESAS-r Cancer is now in use with patients throughout CCA. This valid and reliable PRO measure can be used by other cancer or specialized health care programs who wish to routinely assess common symptoms.

High Symptom Burden in Patients Receiving Radiotherapy and Factors Associated with Being Offered an Intervention

Patient report outcomes are commonly collected during oncology visits to elicit symptom burden and guide management. We aimed to determine the frequency of intervention for patients undergoing radiotherapy with high symptom complexity scores and identify which factors are associated with being offered an intervention. A retrospective chart audit was completed of adult patients with cancer who had at least one radiotherapy appointment and were assigned a high symptom complexity. A total of 200 patients were included; 150 (75.0%) patients were offered an intervention for the main symptom. The most offered intervention was medications. Multivariable logistic regression showed factors associated with being offered an intervention were the following: symptom score of 9 (OR = 9.56, 95% CI 1.64-62.8) and 10 (OR = 7.90, 95% CI 1.69-38.2); palliative intent radiation (OR 3.87, 96% CI 1.46-11.1); and last review appointment (OR 6.22, 95% CI 1.84-23.3). Symptoms associated with being offered an intervention included pain (OR 22.6, 95% CI 6.47-91.1), nausea (OR 15.7, 95% CI 1.51-412), shortness of breath (OR 7.97, 95% CI 1.20-63.7), and anxiety (OR 6.69, 95% CI 1.58-31.6). This knowledge will help guide clinical practice to understand symptom burden and how we can improve our management of patients' symptoms.

Symptom profiles and related factors among patients with advanced cancer: A latent profile analysis

Objective

This study aimed to investigate symptom subgroups and associated influencing factors in patients with advanced cancer.

Methods

A cross-sectional study was conducted, involving 416 patients with advanced cancer. The study examined five symptoms: fatigue, pain, sleep impairment, anxiety, and depression. Latent Profile Analysis (LPA) was utilized to classify symptom subgroups. A multiple logistic regression analysis was conducted to explore factors associated with the identified symptom subgroups.

Results

The analysis revealed three distinct subgroups among the participants: "all low" (58.2%), characterized by normal symptoms except for moderate sleep quality; "all moderate" (35.1%), exhibiting normal symptoms except for poor sleep quality and fatigue; and "all high" (6.7%), experiencing normal pain, moderate depression, moderate anxiety, poor sleep quality, and fatigue. Malnutrition risk, cancer diagnosis, and cancer survivorship duration were found to be associated with a more severe symptom burden.

Conclusions

Patients in the "all high" subgroup faced an increased risk of malnutrition and a longer cancer survivorship duration. Additionally, patients in the "all moderate" subgroup were distinguished by having a breast cancer diagnosis. These findings have significant implications for allocating medical resources and implementing person-centered symptom management strategies.

Patient-Reported Symptom Complexity and Acute Care Utilization Among Patients With Cancer: A Population-Based Study Using a Novel Symptom Complexity Algorithm and Observational Data

BACKGROUND

Patients with cancer in Canada are often effectively managed in ambulatory settings; however, patients with unmanaged or complex symptoms may turn to the emergency department (ED) for additional support. These unplanned visits can be costly to the healthcare system and distressing for patients. This study used a novel patient-reported outcomes (PROs)-derived symptom complexity algorithm to understand characteristics of patients who use acute care, which may help clinicians identify patients who would benefit from additional support.

PATIENTS AND METHODS

This retrospective observational cohort study used population-based linked administrative healthcare data. All patients with cancer in Alberta, Canada, who completed at least one PRO symptom-reporting questionnaire between October 1, 2019, and April 1, 2020, were included. The algorithm used ratings of 9 symptoms to assign a complexity score of low, medium, or high. Multivariable binary logistic regressions were used to evaluate factors associated with a higher likelihood of having an ED visit or hospital admission (HA) within 7 days of completing a PRO questionnaire.

RESULTS

Of the 29,133 patients in the cohort, 738 had an ED visit and 452 had an HA within 7 days of completing the PRO questionnaire. Patients with high symptom complexity had significantly higher odds of having an ED visit (OR, 3.10; 95% CI, 2.59-3.70) or HA (OR, 4.20; 95% CI, 3.36-5.26) compared with low complexity patients, controlling for demographic covariates.

CONCLUSIONS

Given that patients with higher symptom complexity scores were more likely to use acute care, clinicians should monitor these more complex patients closely, because they may benefit from additional support or symptom management in ambulatory settings. A symptom complexity algorithm can help clinicians easily identify patients who may require additional support. Using an algorithm to guide care can enhance patient experiences, while reducing use of acute care services and the accompanying cost and burden.

Symptom Burden and Complexity in the Last 12 Months of Life among Cancer Patients Choosing Medical Assistance in Dying (MAID) in Alberta, Canada

Background: In 2019, cancer patients comprised over 65% of all individuals who requested and received Medical Assistance in Dying (MAID) in Canada. This descriptive study sought to understand the self-reported symptom burden and complexity of cancer patients in the 12 months prior to receiving MAID in Alberta. Methods: Between July 2017 and January 2019, 337 cancer patients received MAID in Alberta. Patient characteristics were descriptively analyzed. As such, 193 patients (57.3%) completed at least one routine symptom-reporting questionnaire in their last year of life. Mixed effects models and generalized estimating equations were utilized to examine the trajectories of individual symptoms and overall symptom complexity within the cohort over this time. Results: The results revealed that all nine self-reported symptoms, and the overall symptom complexity of the cohort, increased as patients’ MAID provision date approached, particularly in the last 3 months of life. While less than 20% of patients experienced high symptom complexity 12 months prior to MAID, this increased to 60% in the month of MAID provision. Conclusions: Cancer patients in this cohort experienced increased symptom burden and complexity leading up to their death. These findings could serve as a flag to clinicians to closely monitor advanced cancer patients’ symptoms, and provide appropriate support and interventions as needed.

Utilizing Patient Reported Outcome Measures (PROMs) in ambulatory oncology in Alberta: Digital reporting at the micro, meso and macro level

Cancer patients experience numerous distressing symptoms and concerns across the course of their illness, which negatively influence their quality of life. Regardless of cancer type, unmanaged symptoms can lead to adverse downstream consequences. Patient Reported Outcome Measures (PROMs) can be used to inform patient care and lead to targeted symptom management but simply gathering this information does not improve outcomes for the patient. Patient generated information must be easy for the clinicians to access and interpret if it is to be used to inform care delivery in ambulatory oncology facilities. This pragmatic work responded to this need. One Canadian provincial ambulatory oncology jurisdiction implemented digital tracking of PROMs over time in the provincial Electronic Medical Record (EMR) to support full integration of PROMs into standard care workflows and processes. Due to an inability within the EMR for direct patient entry, a hybrid data-entry was designed where the patient completes a paper-based PROM in the waiting room, and after clinical review, a clinician documents this along with their clinical assessment in the EMR. Several digital dashboards were developed which report PROMs data at the micro (individual), meso (clinic) and macro (program) levels. Using PROMs routinely in these provincial practice settings has numerous benefits including enhanced patient-clinician communication, assisting with problem detection, management of symptoms, and improving outcomes for patients. There are over 60,000 unique patients represented in our PROMs database, and over 300,000 unique screening events captured. The PROMs data is now used at all levels of the provincial cancer jurisdiction to provide targeted person centred care (micro), to staff appropriately at a clinic or program level (meso), and for capacity planning for provincial programs (macro). A new provincial EMR is currently being implemented which has an associated patient portal. Based on the success of this work, integration of direct entry of PROMs by the patient prior to the appointment and an associated workflow for symptom management is underway in this jurisdiction.

Using Autoregressive Integrated Moving Average (ARIMA) Modelling to Forecast Symptom Complexity in an Ambulatory Oncology Clinic: Harnessing Predictive Analytics and Patient-Reported Outcomes

An increasing incidence of cancer has led to high patient volumes and time challenges in ambulatory oncology clinics. By knowing how many patients are experiencing complex care needs in advance, clinic scheduling and staff allocation adjustments could be made to provide patients with longer or shorter timeslots to address symptom complexity. In this study, we used predictive analytics to forecast the percentage of patients with high symptom complexity in one clinic population in a given time period. Autoregressive integrated moving average (ARIMA) modelling was utilized with patient-reported outcome (PRO) data and patient demographic information collected over 24 weeks. Eight additional weeks of symptom complexity data were collected and compared to assess the accuracy of the forecasting model. The predicted symptom complexity levels were compared with observation data and a mean absolute predicting error of 5.9% was determined, indicating the model’s satisfactory accuracy for forecasting symptom complexity levels among patients in this clinic population. By using a larger sample and additional predictors, this model could be applied to other clinics to allow for tailored scheduling and staff allocation based on symptom complexity forecasting and inform system level models of care to improve outcomes and provide higher quality patient care.

The Use of Patient-Reported Outcome Measures in Phase I Oncology Clinical Trials

OBJECTIVE

To investigate patient-reported outcome (PRO) usage in phase I oncology clinical trials, including types of PRO measures and changes over time.

METHODS

We analyzed ClinicalTrials.gov records of phase I oncology clinical trials completed by December 2019.

RESULTS

Of all eligible trials, 2.3% (129/5,515) reported ≥1 PRO, totaling 181 instances of PRO usage. PRO usage increased over time, from 0.6% (trials initiated before 2000) to 3.4% (trials starting between 2015 and 2019). The most common PRO measures were unspecified (29%), tumor-specific (24%), and generic cancer (19%).

CONCLUSION

Although uncommon in phase I oncology clinical trials, PRO usage is increasing over time. PRO measures were often unspecified on ClinicalTrials.gov, suggesting that more precise reporting and standardization are needed.