Real-world impact of patient-reported outcome measurement on overall survival, healthcare use and treatment discontinuation in cancer patients
Publication: Journal of Comparative Effectiveness Research
Abstract
Aim: The purpose of this retrospective, population-based, observational cohort analysis was to assess whether routine patient-reported outcomes (PRO) monitoring alone has an impact on real-world overall survival (OS) and hospitalizations among individuals diagnosed with lung, breast or colorectal cancer. The importance of follow-up care in post-PRO data collection was also discussed. Patients & methods: Administrative databases covering 17 cancer centers from Alberta, Canada were queried and individuals ≥18 years old and diagnosed with lung, breast or colorectal cancer from 1 January 2016 to 31 December 2019 were included and followed until 31 December 2020. Patients were stratified by whether they received routine PRO monitoring initiated within 120 days of diagnosis and matched 1:1 with use of propensity scores based on baseline characteristics. OS was assessed from the index date to death, and the respective Kaplan–Meier curves were estimated along with hazard ratios from Cox Proportional Hazard Models. Linear and logistic regression models were used to estimate mean differences and odds ratios (OR) respectively for healthcare resource utilization events including cancer physician visits, emergency department visits and outpatient ambulatory care encounters. Results: 4800 patients were included in each matched cohort. There was no statistically significant difference between PRO monitoring and non-monitoring cohorts in OS (HR = 1.01; 95% CI: 0.93–1.09; p = 0.836) and treatment discontinuation (OR = 0.98; 95% CI: 0.85–1.12; p = 0.75). Median OS was 51.5 months for unmonitored cohort (95% CI: 47.5–NA) versus 50.6 months for monitored cohort (95% CI: 47.6–55.7). Compared with PRO-monitored patients, unmonitored patients were associated with lower hospitalization risks (OR = 1.12; 95% CI: 1.03–1.22; p = 0.01). However, PRO-monitored patients experienced significantly fewer physician visits in comparison to unmonitored patients (MD = -1.036; 95% CI: -1.288 to -0.784, p < 0.001). Conclusion: Our results show that capturing patient-reported symptoms alone reduced the number of physician visits but neither reduced hospitalizations nor improved OS in this real-world cancer population. To drive more meaningful clinical impact, PRO monitoring programs must be met with rigorous follow-up response to the identified symptoms.
Tweetable abstract
Capturing patient-reported cancer symptoms alone reduced physician visits but neither reduced hospitalizations nor improved overall survival. To drive more meaningful clinical impact, PRO monitoring programs must be connected closely to care in response to identified symptoms.
Plain language summary
What is this article about?
Despite compelling evidence supporting their use, patient-reported outcomes (PROs) are not widely integrated into routine oncology care. This study aimed to assess whether routine PRO monitoring alone has an impact on real-world overall survival (OS) and hospitalizations among individuals diagnosed with lung, breast, or colorectal cancer.
What were the results?
Our results show that capturing patient-reported symptoms alone reduced the number of physician visits but neither reduced hospitalizations nor improved OS in this real-world cancer population.
What do the results mean?
Patient-reported outcome measures can supplement clinical outcomes and indicators for provincial and worldwide reporting, allowing healthcare systems to become more patient-centered and value-based, improving the quality of life of patients. Our results suggest that capturing patient-reported symptoms alone reduced the number of physician visits but neither reduced hospitalizations nor improved OS in this real-world cancer population. To drive more meaningful clinical impact, PRO monitoring programs must be connected closely to care in response to identified symptoms.
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References
Papers of special note have been highlighted as: • of interest; •• of considerable interest
1.
Weldring T, Smith SM. Patient-reported outcomes (PROs) and patient-reported outcome measures (PROMs). Health Serv. Insights 6, 61–68 (2013).
2.
Greene SM, Tuzzio L, Cherkin D. A framework for making patient-centered care front and center. Perm. J. 16(3), 49–53 (2012).
3.
Basch E, Mody GN, Dueck AC. Electronic patient-reported outcomes as digital therapeutics to improve cancer outcomes. JCO Oncology Practice. 16(9), 541–542 (2020).
• In this editorial, the authors discussed the existing evidence, opportunities and challenges in integrating electronic patient-reported outcomes (PROs) into routine practice as digital therapeutics.
4.
Di Maio M. ES19.04 Improving lung cancer survival through tracking of patient reported outcomes. Journal of Thoracic Oncology. 16(3), S85–S86 (2021).
5.
Peipert JD, Efficace F, Pierson R, Loefgren C, Cella D, He J. Patient-reported outcomes predict overall survival in older patients with acute myeloid leukemia. J. Geriatr. Oncol. 13(7), 935–939 (2022).
•• Using data from one of the largest trials reporting health-related quality of life in older patients with acute myeloid leukemia (AML), the study shows that PROs predict overall survival among older AML patients not suitable for intensive therapy.
6.
Basch E, Deal AM, Dueck AC et al. Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine cancer treatment. JAMA 318(2), 197–198 (2017).
•• This clinical trial shows that Integration of patient-reported outcomes into the routine care of patients with metastatic cancer was associated with increased survival compared with usual care.
7.
Barbera L, Sutradhar R, Seow H et al. Impact of standardized Edmonton symptom assessment system use on emergency department visits and hospitalization: results of a population-based retrospective matched cohort analysis. JCO Oncol. Pract. 16(9), e958–e965 (2020).
•• This real-world study suggests that standardized symptom assessment via the Edmonton Symptom Assessment System (ESAS) is independently associated with decreased rates of ED visits and hospitalizations in cancer patients.
8.
Barbera L, Sutradhar R, Seow H et al. The impact of routine Edmonton Symptom Assessment System (ESAS) use on overall survival in cancer patients: results of a population-based retrospective matched cohort analysis. Cancer Medicine. 9(19), 7107–7115 (2020).
•• This real-world study shows that standardized symptom assessment via the Edmonton Symptom Assessment System (ESAS) is associated with improved survival in cancer patients.
9.
Yadav K, Lewis RJ. Immortal time bias in observational studies. JAMA 325(7), 686–687 (2021).
10.
Gorlach MG, Schrage T, Bokemeyer C et al. Implementation analysis of patient reported outcomes (PROs) in oncological routine care: an observational study protocol. Health Qual. Life Outcomes. 18(1), 3 (2020).
11.
Cuthbert CA, Watson L, Xu Y, Boyne DJ, Hemmelgarn BR, Cheung WY. Patient-reported outcomes in Alberta: rationale, scope, and design of a database initiative. Curr. Oncol. 26(4), e503–e509 (2019).
12.
Mi X, Hammill BG, Curtis LH, Lai EC, Setoguchi S. Use of the landmark method to address immortal person-time bias in comparative effectiveness research: a simulation study. Stat. Med. 35(26), 4824–4836 (2016).
13.
Quan H, Sundararajan V, Halfon P et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med. Care 43(11), 1130–1139 (2005).
14.
Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm. Stat. 10(2), 150–161 (2011).
15.
Lunt M. Selecting an appropriate caliper can be essential for achieving good balance with propensity score matching. Am. J. Epidemiol. 179(2), 226–235 (2013).
16.
Hedges LV, Tipton E, Johnson MC. Robust variance estimation in meta-regression with dependent effect size estimates. Res. Synth. Methods. 1(1), 39–65 (2010).
17.
Penedo FJ, Oswald LB, Kronenfeld JP, Garcia SF, Cella D, Yanez B. The increasing value of eHealth in the delivery of patient-centred cancer care. Lancet Oncol. 21(5), e240–e251 (2020).
18.
Terner M, Louie K, Chow C, Webster G. Advancing PROMs for health system use in Canada and beyond. Journal of Patient-Reported Outcomes. 5(2), 94 (2021).
19.
Watson L, Delure A, Qi S et al. Utilizing patient reported outcome measures (PROMs) in ambulatory oncology in Alberta: digital reporting at the micro, meso and macro level. Journal of Patient-Reported Outcomes. 5(2), 97 (2021).
• This work provides a pragmatic approach to the visualization of PROMs and proposes the ability to improve symptom management capacity within existing cancer care resources.
20.
Hernan MA, Robins JM. Per-protocol analyses of pragmatic trials. N. Engl. J. Med. 377(14), 1391–1398 (2017).
21.
Mansournia MA, Etminan M, Danaei G, Kaufman JS, Collins G. Handling time varying confounding in observational research. BMJ. 359, (2017).
22.
Cain LE, Robins JM, Lanoy E, Logan R, Costagliola D, Hernán MA. When to start treatment? A systematic approach to the comparison of dynamic regimes using observational data. Int. J. Biostat. 6(2), Article 18 (2010).
23.
Hernan MA. How to estimate the effect of treatment duration on survival outcomes using observational data. BMJ. 360, (2018).
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© 2023 Roche Diagnostics. This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License
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Received: 21 April 2023
Accepted: 25 July 2023
Published online: 9 August 2023
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Real-world impact of patient-reported outcome measurement on overall survival, healthcare use and treatment discontinuation in cancer patients. (2023) Journal of Comparative Effectiveness Research. DOI: 10.57264/cer-2023-0061
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- Ethan Basch, Kathryn Hudson, Gabrielle Rocque, Implementation of electronic patient-reported outcomes for symptom monitoring during cancer treatment: the importance of getting it right, Journal of Comparative Effectiveness Research, 10.57264/cer-2023-0157, 12, 12, (2023).
