Patient Reported Outcomes/Metrics Program Trial (PROMPT)—palliative radiation: protocol of a prospective observational feasibility study
Study Protocol | Symptom Management in Palliative Medicine and Palliative Care

Patient Reported Outcomes/Metrics Program Trial (PROMPT)—palliative radiation: protocol of a prospective observational feasibility study

Hiba Othman1,2 ORCID logo, Breffni Hannon1,2, Zhihui Amy Liu1,3, Srinivas Raman4,5, Edel Sexton1, Cory Kasper6, Héloïse Auger7, Chiaojung Jillian Tsai1,2, Aisling Barry8,9, Philip Wong1,2

1Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; 2Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada; 3Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; 4Department of Radiation Oncology, BC Cancer Vancouver, Vancouver, BC, Canada; 5Division of Radiation Oncology, University of British Columbia, Vancouver, BC, Canada; 6Zamplo Inc., Calgary, AB, Canada; 7Carré Technologies Inc. (dba Hexoskin), Montreal, QC, Canada; 8Cancer Research @UCC, School of Medicine, University College Cork, Cork, Ireland; 9Department of Radiation Oncology, Cork University Hospital, Cork, Ireland

Contributions: (I) Conception and design: B Hannon, ZA Liu, C Kasper, A Barry, P Wong; (II) Administrative support: B Hannon, ZA Liu, C Kasper, H Auger, A Barry, P Wong; (III) Provision of study materials or patients: H Othman, E Sexton, CJ Tsai, C Kasper, P Wong; (IV) Collection and assembly of data: H Othman, B Hannon, E Sexton, CJ Tsai, P Wong; (V) Data analysis and interpretation: B Hannon, ZA Liu, S Raman, E Sexton, C Kasper, H Auger, A Barry, P Wong; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Philip Wong, MDCM, MSc. Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, ON, M5G 2M9, Canada; Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada. Email: Philip.wong4@uhn.ca.

Background: Palliative radiotherapy (RT) is commonly used to relieve symptoms and improve quality of life (QOL) for patients with metastatic cancer. Timely recognition of treatment related symptoms and adverse events (AEs), however, remains challenging, as reporting often depends on clinic visits and patient recall. This study explores the feasibility of integrating biometric monitoring, specifically the smart shirt from the Hexoskin Medical System (HMS), to monitor patients with metastatic cancer receiving palliative RT for symptom management. This is complemented by Zamplo, a digital health platform to allow patients and caregivers to report symptoms and well-being.

Methods: The PROMPT trial is a prospective observational feasibility study that aims to recruit 100 patients with metastatic cancer undergoing palliative RT. Adult patients with a confirmed cancer diagnosis who can wear the HMS shirt and use the Zamplo platform are included. To improve accessibility and trial opportunity, patients are fitted with one of 11 sex-adjusted HMS shirt sizes, provided a smartphone, and taught to use Zamplo account. Patients are encouraged to wear the HMS shirt for a minimum of 4 hours daily at baseline, during RT and periodically during follow-up. Patient-reported outcomes (PROs) are being collected using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), the EuroQol 5-Dimension 5-Level, the Person-Centred Coordinated Care Experiences Questionnaire for Cancer Patients (PCC-CA-6), and Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events through Zamplo at baseline and on days 30, 90 and 365, and through ad-hoc patient entries. Zamplo data are complemented with routine clinical symptom screening using ESAS. The primary endpoint is to recruit 100 patients within a 12-month period and to report the frequency of grade 2 or above AEs within 30 days of RT.

Discussion: HMS shirt may improve detection and timely management of RT-related AEs and help identify key biometric variables that predict or correspond to AEs and changes in patient well-being. Whereas patients typically accept wearing wrist-worn activity trackers (ATs), this study will determine whether remote monitoring using the HMS shirt is acceptable and feasible in a palliative cancer population.

Trial Registration: ClinicalTrials.gov, NCT04983199.

Keywords: Palliative; biometric; mobile health app; radiotherapy (RT); metastatic cancer

Submitted Feb 20, 2025. Accepted for publication Jul 29, 2025. Published online Nov 21, 2025.

doi: 10.21037/apm-25-19

Introduction

Palliative radiotherapy (RT) represents a substantial proportion of radiation oncology practice, comprising 25–40% of cases seen in radiation oncology departments in Canada (1). With advances in systemic therapies, patients with metastatic disease are living longer, underlining the importance of palliative RT in interdisciplinary care to enhance well-being, control symptoms, and improve quality of life (QOL) (2). Accurate assessment of pain, QOL, and adverse events (AEs), however, is challenging in practice without burdening patients with frequent visits. Moreover, under-reporting of pain, patient recall, and the fluctuating nature of cancer pain intensity further complicate symptom assessment (3-5).

The importance of patient-derived data is increasingly recognized for its ability to guide preventative measures, holistic patient management and patient engagement in their own healthcare. Collection and use of patient-reported outcomes (PROs) and Patient-Generated Health Data (PGHD) are now routinely done across cancer centres (6), with the expectation that integrating and responding to PGHD will improve patient survival and well-being. Modern technologies, such as the Internet of Things (IoT), provide means to include biometric sensors within PGHD to augment the type and number of data that patients can provide during their daily free-living. Together, biometry and PGHD have transformative potential to help physicians deliver better patient-centered care by accounting for and responding to the patient’s condition beyond pre-planned medical visits.

In oncology, selecting the right cancer treatment, including the schedule and technique of RT, often relies on understanding a patient’s likely prognosis. Yet, this prediction is imprecise and often based on rough estimates of a patient’s performance status at the time of consultation (3-5). Activity trackers (ATs) record key biometrics like daily steps, heart rate, and sleep patterns. Numerous clinical trials have found it feasible to integrate wrist-worn ATs to objectively assess patient biometrics in predicting clinical outcomes, including survival, QOL, and treatment tolerance (7-10). Although we had previously found that patients with metastatic cancer receiving palliative RT accept and adhere to wearing wrist-worn ATs (11), in this study, we will examine the acceptance and feasibility of this patient population in wearing the Hexoskin Medical System (HMS shirt). The HMS shirt, known for its user-friendliness and comfort, captures essential physiological data via embedded sensors that capture information beyond wrist-worn ATs, offering a non-intrusive, augmented approach to continuous remote monitoring (12-14). Should patients find it acceptable and are compliant to wearing the HMS shirt, key digital biometric variables associated with patient well-being and outcomes will be used for future studies to test and validate digital biomarkers in cancer patients.

In this study, we will examine the ability to recruit 100 patients over 12 months as well as assessing the frequency of grade ≥2 RT-related AEs with extended monitoring. We will also evaluate feasibility outcomes including reasons for trial refusal, follow-up and survey completion rates, patient experience and satisfaction, adherence to the Hexoskin shirt, and the feasibility of biometric data collection in this population. Patients will be provided with smartphones and Zamplo accounts to complete electronic PROMs.

Methods

Trial status

The trial started recruitment on December 5, 2022.

Study design

PROMPT is a single-institution, observational study. PROMPT was approved by the Research Ethics Board (REB) of the University Health Network (UHN REB#21-5322.2). The study will be conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Informed consent from subjects will be obtained following a discussion with a clinical research coordinator and by signing the REB-approved informed consent document.

Data collection

Data are collected through surveys and tasks on the Zamplo health platform and through the HMS shirt. Captured data are not intended to interfere with or formulate changes to standard of care treatment and follow-up. All patients are provided with an HMS shirt kit including a size fitted smart shirt (11 sizes per sex), a recorder, a smartphone with the HMS shirt and Zamplo mobile applications, a USB charger and a patient notebook containing instructions for use. Patients are taught to use the HMS shirt and the Zamplo platform, which can also be accessed via a desktop internet browser. Feasibility is defined by two co-primary objectives; the ability to recruit 100 patients over 12 months and assessing the frequency of grade ≥2 RT-related AEs with extended monitoring. Secondary objectives include evaluating quality-adjusted life years (QALY), health-related QOL, reasons for trial refusal, follow-up and survey completion rates, patient satisfaction and adherence to HMS shirt use. Acceptability is not assessed via formal qualitative methods in this pilot phase. Instead, adherence to Hexoskin shirt use and patient-reported outcome measures (PROMs) completion will serve as quantitative indicators of acceptability.

Patients

Patients 18 years or older with a confirmed diagnosis of metastatic cancer for which palliative RT is indicated for symptom management and are able to comfortably wear the HMS shirt and use the Zamplo platform, either independently or with caregiver assistance, are eligible. Additionally, patients must be willing to complete questionnaires and have a life expectancy of at least 3 months. Conversely, patients with significant cognitive or psychiatric impairments hindering therapy or follow-up, pregnant women, those allergic to polyester or synthetic fibers, and patients with pacemakers or implantable cardioverter-defibrillator devices, medically unstable participants and patients receiving whole brain RT for brain metastases at the time of enrolment are excluded, with the exception of previously treated brain metastases patients meeting other eligibility criteria. Palliative RT doses include any of the following regimens: 6–8 Gy in 1 fraction, 20 Gy in 5 fractions, 30 Gy in 10 fractions, 20 Gy in 8 fractions, and 18–24 Gy in 3 fractions given on days 0, 7 and 21).

HMS shirt/biometry monitoring

Patients are encouraged to wear the HMS for at least 4 hours per day during the RT process. Following the completion of RT, patients are asked to wear the HMS for at least 4 consecutive hours once a week. In addition, they are asked to wear the HMS for at least 4 consecutive hours 1–2 days prior to preplanned virtual or telephone visits. Finally, they are encouraged to wear the HMS as often as possible during the first 30 days of the study period. Although adherence is not a designated primary outcome, it will be evaluated as part of the overall feasibility assessment. The HMS shirt is a machine-washable garment embedded with textile electrodes which provide a 3-lead continuous electrocardiogram. It is also designed with respiratory sensors based on the respiratory inductance plethysmography technology and equipped with a highly accurate 3-axis accelerometer (Figure 1).

Figure 1 Hexoskin medical system. The Hexoskin medical system is a smart garment that measures various activity, cardiac and respiratory metrics when worn by the study participants. Image reproduced with permission from Hexoskin. ECG, electrocardiogram; RIP, respiratory inductance plethysmography.

Health app platform—Zamplo

Zamplo is a comprehensive digital platform for PRO reporting and patient self-management (15). This Canadian platform has innovative features such as “My Health Routines” that help patients record a variety of PROs in a single quick entry form, including symptom type and severity, as well as medications and health data (Figure 2). Additionally, through the “Caregiver Access” feature, caregivers can enter PROs in situations when the patient is unable to do so. Proxy completion of PROMs is recorded within the application and explicitly distinguished from patient entries. The use of proxies and rates of proxy versus patient entries are captured and included in the overall feasibility and adherence assessment. All entries are automatically date- and time-stamped and reference the data source. Security measures are already in place within Zamplo to safeguard personal health information. Zamplo follows the Personal Information Protection and Electronic Documents Act, the Canadian law relating to data privacy.

Figure 2 Zamplo. The Zamplo digital health platform allows study participants to answer PROMPT patient surveys, their own personal information and routines into their personal accounts. Participants can grant access to their personal accounts to caregivers, who can then answer surveys and routines on behalf of the participants. Image reproduced with permission from Zamplo Inc. PROMPT, Patient Reported Outcomes/Metrics Program Trial.

Assessments and follow-up

At baseline (pre-RT), 30-day follow-up, 90-day follow-up and 365-day follow-up, the following surveys are administered to patients through Zamplo along with scheduled virtual or telephone visits at these corresponding intervals (Table 1). These surveys include the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), a validated questionnaire assessing cancer patients’ QOL; the EuroQol 5-Dimension 5-Level (EQ-5D-5L), a standardized measure evaluating health-related QOL across five dimensions; the Person-Centred Coordinated Care Experiences Questionnaire for Cancer Patients (PCC-CA-6), which assesses patient satisfaction with care quality in six core areas; and the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE), which includes subjective evaluations of symptoms and AEs, such as nausea, vomiting, diarrhea, shortness of breath, radiation skin reaction, general pain, and fatigue. Patients are also encouraged to maintain symptom journals. In addition, all patients attending outpatient clinics at the cancer centre routinely complete symptom screening using the Edmonton Symptom Assessment System (ESAS). These data will also be used for the purpose of this study.

Table 1

PROMPT study schedule

Assessments Baseline 30-day follow-up (±7 days) 90-day follow-up (±7 days) 365-day follow-up (±14 days)
Patient pre-screening X
Informed consent of patient X
Patient eligibility/enrollment/stratification X
Vital signs† X
Hexoskin measurements‡ X
Follow up visit (live/death status, review of symptoms, toxicity, and PROs) X X X X
Zamplo (patient reported events and outcomes) X (continuously collected as patients enter ad-hoc, patients will be asked to answer specific study QOL questionnaires 1–2 days prior to each scheduled study visit)
Hexoskin Medical System X (continuously recording, patients will be asked to wear at least once a week during the first 30 days after enrollment, then 1–2 days prior to each scheduled study visit)

†, includes: blood pressure, oxygen saturation, heart rate, respiration rate, ECOG; ‡, includes: height, weight, and body circumference for vest fitting [thorax, naval, chest (if applicable)]. ECOG, Eastern Cooperative Oncology Group; PROs, patient-reported outcomes; PROMPT, Patient Reported Outcomes/Metrics Program Trial; QOL, quality of life.

Outcomes

The primary endpoint is to assess the feasibility of recruiting 100 patients over a 12-month period and to assess the frequency of grade ≥2 RT AEs with extended monitoring during and within 30 days of RT. Secondary endpoints include evaluating Health-Related Quality of Life using the EORTC QLQ-C30 tool and electronic surveys, conducting economic and health technology assessments using EQ-5D-5L data, investigating reasons for trial refusal, estimating rates of completed follow-ups and surveys completion rates, measuring patient experience and satisfaction with the Zamplo platform and adherence to the HMS shirt, and assessing the feasibility of HMS shirt data collection in this patient population. Furthermore, the study aims to measure overall survival, and the AE profile of various RT regimens.

Statistical analysis

The study’s analysis plan includes several components: first, reporting the total number of recruited participants over a 12-month period and assessing the frequency of grade ≥2 RT-related AEs. PROs from EORTC QLQ-C30 at baseline and each follow up time will be displayed longitudinally using spaghetti plots, with trends over time estimated using linear mixed effects models. EQ-5D-5L responses will be converted into utilities using the Canadian value set and QALY will be calculated by multiplying the number of life-years in each health state with a utility that reflects the QOL in that state, aggregated over all the health states of the entire study period. Reasons for trial refusal and follow-up rates will be qualitatively summarized, and patient feedback will be evaluated descriptively. The frequency (number of times per week) and duration (number of hours per day) patients are wearing the HMS shirt during the first month, and over the entire study period, mobile app QOL survey completion rates, and overall survival will be reported. Median survival time will be estimated using the Kaplan-Meier (KM) method with 95% confidence intervals. Additionally, AEs by grade and the incremental cost-effectiveness ratio (ICER) will be assessed, calculating the difference in expected cost and proportion of grade ≥2 AEs between HMS shirt and standard of care.

Discussion

Patients receiving palliative RT often experience fluctuating symptoms that are difficult to monitor between clinic visits. This study was designed to assess whether combining wearable biometric monitoring using the HMS shirt with structured PROs through the Zamplo health platform could offer a practical approach to improving symptom tracking in this setting. It may provide early insights into how such technologies might be integrated into routine palliative cancer care to support timely symptom management and enhance patient engagement.

Complementing subjective electronically captured PROs with objective measures such as respiratory rate, pulse rate, activity level, and sleep patterns could provide a comprehensive evaluation of the effects of palliative RT with real-time detection of potential complications and toxicity and the acute need for analgesic adjustments that can result from successful palliative RT. Gresham et al. found a significant correlation between activity metrics and PROs in patients with metastatic or incurable cancer (16). Furthermore, wrist ATs have been applied to identify toxicities from immune checkpoint blockade and stereotactic body RT, with encouraging acceptance rates (17). In our pilot study with 12 palliative RT patients, we observed their positive response to wearing wrist ATs for 14 days and the prognostic value of baseline metrics on survival and QOL (11). Outside of cancer, the UK Biobank Study (18) demonstrated the populational acceptance of wrist-worn accelerometers and their data is starting to show utility in the early detection of Parkinson’s disease (19).

The above-mentioned studies point to the feasibility of establishing effective virtual care for palliative cancer patients. However, a robust foundation for effective virtual care requires a nuanced understanding of the available technologies to determine which virtual means are most suitable to safely monitor and care for different patient populations. In this context, the HMS shirt was examined as its promising smart shirt captures a wealth of physiological data via embedded sensors, offering a non-intrusive approach to continuous monitoring (13,14). To complement the HMS shirt, the Zamplo health platform was deployed as the patient-facing tool to acquire PROs using smartphones, tablets or personal computers. To improve digital accessibility and privacy protection, patients are offered a smartphone pre-installed with Zamplo and institutional security features that allow the institution and research team to remotely remove all personal information from the device. Moreover, as a tool to help improve patient engagement and overall compliance wearing the device, daily summaries of smart shirt biometrics are included as journal entries in the patient’s Zamplo account.

Patients with cancer, in particular, stand to benefit from wearable monitoring devices. Real-time personalized approach to patient free-living signs and PROs aligns with the principles of precision medicine and can lead to improved patient outcomes (20-22). Development of digital biomarkers and timely remote monitoring would allow providers to treat only when needed, to avoid for example the use of prophylactic steroids against palliative RT pain flares, which may diminish the efficacy of immune-checkpoint inhibitors which are becoming ubiquitous in cancer patient care (23). As more patients are living with cancer as a chronic condition, PGHD and tools will become essential to improve communication between providers and patients to optimize the management of symptoms and side-effects beyond planned in-person visits (24).

In this study, we seek to examine the feasibility of recruiting 100 patients undergoing palliative RT to wear the HMS shirt and use the Zamplo platform as the PRO communication tool. The successful recruitment of a substantial number of patients will demonstrate the potential for conducting research in this population. If achieved, it will affirm the willingness of this patient population to engage with wearable garment technology and digital platforms during their palliative cancer care journey. At our center, we treat around 780 patients with palliative RT each year, which makes it reasonable to aim for recruiting 100 participants over 12 months. Despite our efforts, we acknowledge that achieving our recruitment goal may not be feasible in this context. Understanding the reasons for refusal is an integral part of our study, as it provides valuable insights into the barriers and concerns that patients in palliative care may have regarding the utilization of such technologies. In the event that our recruitment target is not met, we will thoroughly analyze the data and explore the factors contributing to recruitment challenges.

Evolution of technology should be harnessed to develop virtual monitoring solutions adapted for various patient situations. PGHD, wearables, IoT can enhance the accuracy and efficiency of data collection by providers and engage patients to be active participants in their health and well-being. However, the timing, frequency, and means of gathering PGDH must be strategically planned. This involves assessing when and how often data should be collected to maximize clinical insights while minimizing intrusions into patients’ daily lives at home, an important option in palliative care. Correspondingly, strategically timed and targeted data collection can minimize costs and also optimize the utilization of healthcare resources to respond to PGHD. Timely and data-driven interventions facilitated by virtual monitoring can lead to improved patient outcomes through early detection of potential issues and proactive management. In conclusion, the effective implementation of virtual monitoring in healthcare, including palliative cancer patients, requires a strategic blend of cutting-edge technology, thoughtful consideration of data collection practices, a patient-centric approach, and an understanding of the broader impact on the healthcare system. When executed thoughtfully, virtual monitoring has the potential to revolutionize healthcare delivery, providing more accessible, cost-effective, and patient-centered care.

Acknowledgments

None.

Footnote

Peer Review File: Available at https://apm.amegroups.com/article/view/10.21037/apm-25-19/prf

Funding: This study was supported by the Princess Margaret Cancer Foundation.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://apm.amegroups.com/article/view/10.21037/apm-25-19/coif). C.K. is the Chief Technological Officer, on the Board of Directors and a significant shareholder of Zamplo Inc., whose health app was used to collect PROs during the trial. C.J.T. serves on advisory board of Varian Medical Inc. H.A. is a salaried employee of Carré Technologies Inc. (dba Hexoskin), which participated in the collaboration underlying this study. She received no additional financial compensation related to this work. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was approved by the Research Ethics Board (REB) of the University Health Network (UHN REB#21-5322.2). The study will be conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Informed consent from subjects will be obtained following a discussion with a clinical research coordinator and by signing the REB-approved informed consent document.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

  1. Huang J, Wai ES, Lau F, et al. Palliative radiotherapy utilization for cancer patients at end of life in British Columbia: retrospective cohort study. BMC Palliat Care 2014;13:49. [Crossref] [PubMed]
  2. Mollica MA, Smith AW, Tonorezos E, et al. Survivorship for Individuals Living With Advanced and Metastatic Cancers: National Cancer Institute Meeting Report. J Natl Cancer Inst 2022;114:489-95. [Crossref] [PubMed]
  3. Adam R, Burton CD, Bond CM, et al. Can patient-reported measurements of pain be used to improve cancer pain management? A systematic review and meta-analysis. BMJ Support Palliat Care 2017;7:0.
  4. Caraceni A, Shkodra M. Cancer Pain Assessment and Classification. Cancers (Basel) 2019;11:510. [Crossref] [PubMed]
  5. Oldenmenger WH, Sillevis Smitt PA, van Dooren S, et al. A systematic review on barriers hindering adequate cancer pain management and interventions to reduce them: a critical appraisal. Eur J Cancer 2009;45:1370-80. [Crossref] [PubMed]
  6. Stetson PD, McCleary NJ, Osterman T, et al. Adoption of Patient-Generated Health Data in Oncology: A Report From the NCCN EHR Oncology Advisory Group. J Natl Compr Canc Netw 2022; [Crossref] [PubMed]
  7. Gresham G, Schrack J, Gresham LM, et al. Wearable activity monitors in oncology trials: Current use of an emerging technology. Contemp Clin Trials 2018;64:13-21. [Crossref] [PubMed]
  8. O'Connor B, Markicevic M, Newman L, et al. Clinical utility of portable electrophysiology to measure fatigue in treatment-naïve non-small cell lung cancer. Support Care Cancer 2019;27:2617-23. [Crossref] [PubMed]
  9. Thomas S, Walsh D, Shrotriya S, et al. Symptoms, Quality of Life, and Daily Activities in People With Newly Diagnosed Solid Tumors Presenting to a Medical Oncologist. Am J Hosp Palliat Care 2017;34:611-21. [Crossref] [PubMed]
  10. Chow R, Drkulec H, Im JHB, et al. The Use of Wearable Devices in Oncology Patients: A Systematic Review. Oncologist 2024;29:e419-30. [Crossref] [PubMed]
  11. Dorion V, Lambert L, Frazzi A, et al. A Pilot Study in the Use of Activity Trackers for Assessing Response to Palliative Radiotherapy. Cureus 2017;9:e1871. [Crossref] [PubMed]
  12. Chaari M, Abid M, Ouakrim Y, et al. A mobile application for physical activity recognition using acceleration data from wearable sensors for cardiac rehabilitation. International Conference on Health Informatics 2020.
  13. Lewthwaite H, D'Elia G, Johnson S, et al. Feasibility of wearable smart shirt technology for daily life physiology and symptom assessment in COPD. European Respiratory Journal 2023;62:PA1589.
  14. Hedge E, Mastrandrea C, Hughson R. Wearable sensors non-intrusively monitor cardiovascular and respiratory adaptation to simulated microgravity. 44th COSPAR Scientific Assembly. Held 16-24 July, 2022.
  15. Deleemans JM, Samnani S, Lloyd C, et al. Improving adherence and health outcomes in testicular cancer survivors using a mobile health-based intervention: A mixed-methods pilot study. Digit Health 2023;9:20552076231167002. [Crossref] [PubMed]
  16. Gresham G, Hendifar AE, Spiegel B, et al. Wearable activity monitors to assess performance status and predict clinical outcomes in advanced cancer patients. NPJ Digit Med 2018;1:27. [Crossref] [PubMed]
  17. Ye R, Bahig H, Wong P. PD-0406 Unsupervised leaning of biometric features predicts metastatic head and neck cancer progression. Radiotherapy and Oncology 2023;182:S308-9. [Crossref]
  18. Doherty A, Jackson D, Hammerla N, et al. Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS One 2017;12:e0169649. [Crossref] [PubMed]
  19. Schalkamp AK, Peall KJ, Harrison NA, et al. Wearable movement-tracking data identify Parkinson's disease years before clinical diagnosis. Nat Med 2023;29:2048-56. [Crossref] [PubMed]
  20. Basch E, Deal AM, Kris MG, et al. Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A Randomized Controlled Trial. J Clin Oncol 2016;34:557-65. [Crossref] [PubMed]
  21. Basch E, Schrag D, Henson S, et al. Effect of Electronic Symptom Monitoring on Patient-Reported Outcomes Among Patients With Metastatic Cancer: A Randomized Clinical Trial. JAMA 2022;327:2413-22. [Crossref] [PubMed]
  22. Denis F, Basch E, Septans AL, et al. Two-Year Survival Comparing Web-Based Symptom Monitoring vs Routine Surveillance Following Treatment for Lung Cancer. JAMA 2019;321:306-7. [Crossref] [PubMed]
  23. Arbour KC, Mezquita L, Long N, et al. Impact of Baseline Steroids on Efficacy of Programmed Cell Death-1 and Programmed Death-Ligand 1 Blockade in Patients With Non-Small-Cell Lung Cancer. J Clin Oncol 2018;36:2872-8. [Crossref] [PubMed]
  24. Brown R, Coventry L, Sillence E, et al. Collecting and sharing self-generated health and lifestyle data: Understanding barriers for people living with long-term health conditions - a survey study. Digit Health 2022;8:20552076221084458. [Crossref] [PubMed]
Cite this article as: Othman H, Hannon B, Liu ZA, Raman S, Sexton E, Kasper C, Auger H, Tsai CJ, Barry A, Wong P. Patient Reported Outcomes/Metrics Program Trial (PROMPT)—palliative radiation: protocol of a prospective observational feasibility study. Ann Palliat Med 2025;14(6):570-578. doi: 10.21037/apm-25-19

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