Population-level evidence of survival benefits of patient-reported outcome symptom monitoring software systems in routine cancer care

SOHO State of the Art Updates and Next Questions | Measuring Patient-Reported Outcomes (PROs) and Treatment Tolerability in Patients With Hematologic Malignancies

There has been a rapid expansion of novel therapeutics for hematologic malignancies, including monoclonal antibodies, small molecules, and cellular therapies, which confer different treatment-related toxicities and symptomatic adverse events (AEs) than traditional cytotoxic chemotherapies. Given that patients with blood cancers are living longer with these newer treatments, with some therapies requiring indefinite or time-intensive administration, consideration of patient-reported tolerability and effects on health-related quality of life (HRQoL) are increasingly relevant. Historically, clinical trials have focused on the efficacy and safety of therapies. While related to safety and not intended to replace it, "treatment tolerability" is a distinct construct defined as the extent to which symptomatic and nonsymptomatic AEs impact a patient's ability and desire to continue with current treatment dosing, which also encompasses how patients feel and function while undergoing anticancer therapies. Assessment of tolerability requires the systematic and rigorous measurement of patient-reported outcomes (PROs). In this review, we discuss the introduction of patient-reported outcomes measures (PROMs) into hematology clinical trials and how PROs inform the measurement of treatment tolerability, including symptomatic adverse events, physical and role functioning, and overall side effect burden. Selected PROMs for measurement of these core tolerability domains are outlined, with a focus on novel analytic tools that have been developed for the longitudinal analysis of tolerability data. Further, we outline ongoing studies to accelerate integration of PROs throughout the cancer care spectrum, from early-stage drug development to routine clinical care, with the goal of improving both HRQoL and survival.

The impact of age on physical functioning after treatment for breast cancer, as measured by patient-reported outcome measures: A systematic review

PURPOSE

This systematic review aims to explore the impact of age on physical functioning post-treatment for early-stage, locally advanced, or locally recurrent breast cancer, as measured by patient-reported outcome measures (PROMs), identify PROMs used and variations in physical functioning terms/labels.

METHODS

MEDLINE, EmBase, PsycINFO, CINAHL and AMED were searched, along with relevant key journals and reference lists. Risk of bias (quality) assessment was conducted using a Critical Appraisal Skills Programme checklist. Data was synthesised through tables and narrative.

RESULTS

28,207 titles were extracted from electronic databases, resulting in 44 studies with age sub-groups, and 120 without age sub-groups. Of those with findings on the impact of age, there was variability in the way findings were reported and 21 % found that age did not have a significant impact. However, 66 % of the studies found that with older age, physical functioning declined post-treatment. Comorbidities were associated with physical functioning declines. However, findings from sub-groups (breast cancer stage, treatment type and time post-treatment) lacked concordance. Twenty-eight types of PROM were used: the EORTC QLQ-C30 was most common (50.6 %), followed by the SF-36 (32.3 %). There were 145 terms/labels for physical functioning: 'physical functioning/function' was used most often (82.3 %).

CONCLUSIONS

Findings point towards an older age and comorbidities being associated with more physical functioning declines. However, it was not possible to determine if stage, treatment type and time since treatment had any influence. More consistent use of the terminology 'physical functioning/function' would aid future comparisons of study results.

Machine learning applied in patient-reported outcome research-exploring symptoms in adjuvant treatment of breast cancer

BACKGROUND

Patient-reported outcome (PRO) data may help us better understand the life of breast cancer patients. We have previously collected PRO data in a national Danish breast cancer study in patients undergoing adjuvant chemotherapy. The aim of the present post-hoc explorative study is to apply Machine Learning (ML) algorithms using permutation importance to explore how specific PRO symptoms influence nonadherence to six cycles of planned adjuvant chemotherapy in breast cancer patients.

METHODS

We here investigate ePRO-data from the 347 patients. The ePRO presented 42 PROCTCAE questions on 25 symptoms. Patients completed the ePRO before each cycle of chemotherapy. Number of patients with completion of the scheduled six cycles of chemotherapy were registered. Two ML models were applied. One aimed at discovering the individual relative importance of the different questions in the dataset while the second aimed at discovering the relationships between the questions. Permutation importance was used.

RESULTS

Out of 347 patients 238 patients remained in the final dataset, 15 patients dropped out. Two symptoms: aching joints and numbness/tingling, were the most important for dropout in the final dataset, each with an importance value of about 0.04. Model's average ROC-AUC-score being 0.706. In the second model a low performance score made the results very unreliable.

CONCLUSION

In conclusion, this explorative data analysis using ML methodologies in an ePRO dataset from a population of women with breast cancer treated with adjuvant chemotherapy unravels that the symptoms aching joints and numbness/tingling could be important for drop out of planned adjuvant chemotherapy.

Assessing Patient-Reported Outcomes in Routine Cancer Clinical Care Using Electronic Administration and Telehealth Technologies: Realist Synthesis of Potential Mechanisms for Improving Health Outcomes

BACKGROUND

The routine measurement of patient-reported outcomes in cancer clinical care using electronic patient-reported outcome measures (ePROMs) is gaining momentum worldwide. However, a deep understanding of the mechanisms underpinning ePROM interventions that could inform their optimal design to improve health outcomes is needed.

OBJECTIVE

This study aims to identify the implicit mechanisms that underpin the effectiveness of ePROM interventions and develop program theories about how and when ePROM interventions improve health outcomes.

METHODS

A realist synthesis of the literature about ePROM interventions in cancer clinical care was performed. A conceptual framework of ePROM interventions was constructed to define the scope of the review and frame the initial program theories. Literature searches of Ovid MEDLINE, Ovid Embase, Scopus, and CINAHL, supplemented by citation tracking, were performed to identify relevant literature to develop, refine, and test program theories. Quality appraisal of relevant studies was performed using the Mixed Methods Appraisal Tool.

RESULTS

Overall, 61 studies were included in the realist synthesis: 15 (25%) mixed methods studies, 9 (15%) qualitative studies, 13 (21%) descriptive studies, 21 (34%) randomized controlled trials, and 3 (5%) quasi-experimental studies. In total, 3 initial program theories were developed regarding the salient components of ePROM interventions-remote self-reporting, real-time feedback to clinicians, and clinician-patient telecommunication. The refined theories posit that remote self-reporting enables patients to recognize and report symptoms accurately and empowers them to communicate these to clinicians, real-time feedback prompts clinicians to manage symptoms proactively, and clinician-patient telephone interactions and e-interactions between clinic encounters improve symptom management by reshaping how clinicians and patients communicate. However, the intervention may not achieve the intended benefit if ePROMs become a reminder to patients of their illness and are not meaningful to them and when real-time feedback to clinicians lacks relevance and increases the workload.

CONCLUSIONS

The key to improving health outcomes through ePROM interventions is enabling better symptom reporting and communication through remote symptom self-reporting, promoting proactive management of symptoms through real-time clinician feedback, and facilitating clinician-patient interactions. Patient engagement with self-reporting and clinician engagement in responding to feedback are vital and may reinforce each other in improving outcomes. Effective ePROM interventions might fundamentally alter how clinicians and patients interact between clinic encounters.

Cancer Care Team's Management of Clinical Alerts Generated by Electronically Collected Patient Reported Outcomes: We Could Do Better

Electronically administered patient-reported outcome measures (ePROMs) are effective digital health tools for informing clinicians about cancer patients' symptoms and facilitating timely patient-centred care. This paper describes the delivery of healthcare activities supported by the PROMPT-Care model, including ePROMs generated clinical alerts, cancer care team (CCT) response to alerts, and patients' perceptions of the CCT response and ePROMs system. This mixed-methods study includes cancer patients from four cancer therapy centres in New South Wales, Australia. Quantitative and qualitative data were collected regarding clinical alert activity, CCT response, and patient perceptions of the CCT responses and ePROMs system. Qualitative data were thematically analysed. Of the 328 participants whose care was informed by the digital health tool, 70.8% (n = 233) generated at least one alert during the trial period, with 877 alerts generated in total. Although 43.7% (n = 383) were actioned by the CCT, at least 80% of participants found follow-up CCT phone calls beneficial, with multiple benefits confirmed in interviews. The cancer care delivery arm of the PROMPT-Care trial involving clinical alerts to the CCT was positively perceived by most participants, resulting in a diverse range of benefits. However, further work is required, informed by implementation science, to improve the percentage of actioned clinical alerts.

Mitigating acute chemotherapy-associated adverse events in patients with cancer

Despite the enthusiasm surrounding novel targeted agents and immunotherapies, chemotherapy remains the mainstay treatment for most human malignancies, either alone or in combination. Yet, the burden of chemotherapy-associated adverse events (CAAEs) remains high and, importantly, is associated with considerable morbidity, mortality and costs that affect patients across multiple dimensions, including physical, emotional and social functioning. CAAEs can directly affect patient outcomes and indirectly increase the risk of cancer recurrence by compromising treatment intensity and continuity. Systematic efforts to identify and critically summarize the evidence on management approaches for CAAEs remain limited. Herein, we review the most common acute CAAEs having a major effect on survival, quality of life, function and/or continuation of optimal therapy. We focus on selected acute toxicities that occur during treatment, summarizing their underlying pathophysiology, multifactorial aetiologies, evidenced-based treatments, prevention strategies and management recommendations. We also summarize the available evidence on risk factors, validated risk assessment tools and other efforts to optimize symptom control in patients most likely to benefit in order to personalize the prevention and treatment of acute CAAEs. Finally, we discuss innovative symptom monitoring and supportive care interventions that are under development to further improve the outcomes of patients with cancer.

Navigating financial toxicity in patients with cancer: A multidisciplinary management approach

Approximately one-half of individuals with cancer face personal economic burdens associated with the disease and its treatment, a problem known as financial toxicity (FT). FT more frequently affects socioeconomically vulnerable individuals and leads to subsequent adverse economic and health outcomes. Whereas multilevel systemic factors at the policy, payer, and provider levels drive FT, there are also accompanying intervenable patient-level factors that exacerbate FT in the setting of clinical care delivery. The primary strategy to intervene on FT at the patient level is financial navigation. Financial navigation uses comprehensive assessment of patients' risk factors for FT, guidance toward support resources, and referrals to assist patient financial needs during cancer care. Social workers or nurse navigators most frequently lead financial navigation. Oncologists and clinical provider teams are multidisciplinary partners who can support optimal FT management in the context of their clinical roles. Oncologists and clinical provider teams can proactively assess patient concerns about the financial hardship and employment effects of disease and treatment. They can respond by streamlining clinical treatment and care delivery planning and incorporating FT concerns into comprehensive goals of care discussions and coordinated symptom and psychosocial care. By understanding how age and life stage, socioeconomic, and cultural factors modify FT trajectory, oncologists and multidisciplinary health care teams can be engaged and informative in patient-centered, tailored FT management. The case presentations in this report provide a practical context to summarize authors' recommendations for patient-level FT management, supported by a review of key supporting evidence and a discussion of challenges to mitigating FT in oncology care. CA Cancer J Clin. 2022;72:437-453.

Challenges in virtual collection of patient-reported data: a prospective cohort study conducted in COVID-19 era

Prior to the COVID-19 pandemic, patients attending ambulatory clinics at cancer centers in Ontario completed the Edmonton Symptom Assessment Scale (ESAS) at each visit. At our center, completion was via touchpad, with assistance from clinic volunteers. As of March 2020, clinic appointments were conducted virtually when possible and touch pads removed. We anticipated a negative impact on the collection of patient-reported outcomes (PROs) and the recognition of severe symptoms.

METHODS

We performed a prospective cross-sectional cohort study to investigate remote ESAS completion by patients with appointments at a weekly surgical oncology clinic. Patients in the initial study cohort were asked to complete and return the ESAS virtually (V). Given low completion rates, the ensuing cohort was asked to complete a hard-copy (HC) ESAS. For the final cohort, we provided remote, personal mentorship by a member of the care team to support virtual electronic ESAS completion (virtual-mentored (VM) cohort).

RESULTS

Between May and July 2020, a total of 174 patient encounters were included in the study. For the V cohort, 20/46 patients (44%) successfully completed and returned the electronic ESAS, compared to 49/50 (98%) for the HC cohort. For the VM cohort, the overall completion rate was 74% (58/78); however, 12 of these 58 patients did not independently complete a virtual ESAS. Virtual questionnaire completion was not predicted by age, sex, or tumor site, although patients who completed the ESAS were more likely to be in active management rather than surveillance (p = 0.04). Of all completed forms, 42% revealed a depression score of ≥2, and 27% an anxiety score of ≥4.

CONCLUSIONS

We identified significant barriers to the virtual completion of ESAS forms, with a lack of predictive variables. The severe degree of psychological distress reported by ~50% of respondents demonstrates the need for ongoing regular collection/review of these data. Innovative solutions are required to overcome barriers to the virtual collection of PROs.

Exploring Noona Using Passively-Collected Data and Satisfaction/Loyalty Ratings

Background

Electronic patient-reported outcomes’ real time communication of treatment-related symptoms is increasingly associated with better outcomes including longer survival and less health care resource use, but the primary method of collecting this information, static questionnaires, has not evolved.

Objective

The aim of this paper is to describe the use of Noona’s three methods of communicating treatment-related symptoms, which are as follows: (1) Noona symptom questionnaires (NSQ), which incorporate branching logic; (2) a diary; and (3) secure messaging, the last two of which have NSQ reporting functionality. It also aims to explore, using multivariable analyses, whether patients find value using these features.

Methods

Noona users (N=1081) who have an active account for more than 30 days, who responded to the satisfaction/loyalty item, and who were undergoing active cancer treatment (systemic or radiotherapy) in the United States were included in this study. All study data were collected via software embedded within Noona code. This includes metadata, patient activities (measured in clicks), and responses to a satisfaction/loyalty question (“How likely are you to recommend Noona to another patient”) displayed on the Noona home page.

Results

Noona users expressed a high degree of satisfaction/loyalty when asked to rate how likely they would recommend Noona to another patient. Multivariable analyses indicate small but significant effects for some of the analyses. Use of NSQs were significantly related to satisfaction/loyalty, users of NSQs had significantly higher satisfaction/loyalty than those who did not use any, and secure communication use was significantly higher for those who rated the app highly compared to those who did not. These relationships will likely be further explicated with the use of satisfaction/loyalty questions that focus specifically on feature use.

Conclusions

Noona is well liked by respondents, and exploratory multivariable analyses demonstrate the potential for using passively and minimally invasive data to demonstrate value.

An Analysis of Clinical Toxic Effects and Quality of Life as a Function of Radiation Dose and Volume After Lung Stereotactic Body Radiation Therapy

Purpose

To analyze clinical toxicity and quality-of-life (QOL) outcomes among patients with stage I non-small cell lung cancer (NSCLC) after stereotactic body radiation therapy (SBRT) as a function of radiation dose and volume parameters.

Methods and Materials

In this institutional review board-approved study, 55 patients with stage I NSCLC who received SBRT (12 Gy × 4) and completed QOL forms were analyzed. Clinical symptoms and QOL outcomes were measured at baseline and at 3, 6, 12, 18, 24, and 36 months after SBRT. Clinical toxicity was graded using the Common Terminology Criteria for Adverse Events, version 4.0. Quality of life was followed using the validated Functional Assessment of Cancer Therapy-Lung-Trial Outcome Index (FACT-L-TOI) instrument. Dosimetric parameters including the mean lung radiation dose and the volume of normal lung receiving greater than 5, 10, 13, or 20 Gy (V₅, V₁₀, V₁₃, and V₂₀) were measured from the radiation treatment plan. Student t tests and Pearson correlation analyses were used to examine the relationships between radiation lung metrics and clinically meaningful changes in QOL and/or clinical toxic effects. The Kaplan-Meier method was used to estimate rates of local control (LC), disease-free survival (DFS), and overall survival (OS).

Results

With a median follow-up of 24 months, the 3-year LC, DFS, and OS were 93%, 65%, and 84%, respectively, with a 5.5% rate of grade-3 toxic effects and no grade 4 or 5 toxic effects. Clinically meaningful declines in patient-reported QOL (FACT-L-TOI, lung cancer subscale, physical well-being, and/or functional well-being) posttreatment significantly correlated with increased dosimetric parameters such as V₁₀, V₁₃, and V₂₀.

Conclusion

Although lung SBRT was associated with excellent LC and minimal clinical toxic effects for early-stage NSCLC, clinically meaningful declines in QOL were significantly correlated with increasing lung dose and volume parameters.

Automated health chats for symptom management of head and neck cancer patients undergoing radiation therapy

OBJECTIVE

To report the early experience using an automated chatbot (Chats)for patient-reported outcomes (PRO) and symptom self-managementinhead and neck cancer (HNC) patients undergoing radiation treatment (RT).

METHODS

Patients aged ≥ 18 yearsdiagnosed with HNC who were scheduled to begin RT were given the option to use Chats from June 2018 to June 2019. Enrolled patients received chat notifications two days before weekly on-treatment visitsand every 1-4 weeks after RT for an additional 4 months. After the first in-person follow-up visit, participants completed an electronic usability and satisfaction questionnaire.

RESULTS

Of 95 patients who agreed to participate, 84 were eligible for analysis.Participantswere significantly younger than patients who declined participation (mean age 61.3 vs 68.3 years;p-value < 0.001). Patient engagement with Chats was highest at 67% during the first month and declined over time (p-value = 0.004). Concordance between PRO and clinician-reported outcomes (CRO) was fair, ranging from 0.10 to 0.43 (Cohen κ statistics). The most commonly under-reported symptoms were salivary duct inflammation (53%), xerostomia (41%), and mucositis (37%). 89% (39 of 44) of patients who completed surveys found Chats easy to use, and 61% reported that Chats helped with symptom self-management and reduced the need to call the care team.

CONCLUSIONS

These early results suggest that an interactive chatbot is feasible and provides support for HNC patients during and after RT. Chats identified discordance between PRO and CRO. Further study is required to measure benefits of Chats in a larger population.