The Emerging Role of Digital Therapeutics in Medical, Surgical and Radiation Oncology
SA-CME credits are available for this article here.
Abstract
Digital therapeutics (DTx) are software interventions of therapeutic value supported by scientific evidence to prevent, manage, and treat a broad spectrum of physical, mental and behavioral conditions. Current data supports integration in the setting of chronic medical conditions such as diabetes, hypertension, opioid dependence, and insomnia. Recent clinical studies have shown emergence of DTx as potential solutions in the cancer care continuum to improve medication adherence, chemotherapy tolerance, and even overall survival. In addition, evidence suggests that these digital interventions may have a significant impact on lowering the cost of health care for current patients and cancer survivors. Given the potential financial toxicity for oncology patients, these modalities, such as digital patient-reported outcomes (PROs), are being actively investigated to determine the economic benefits as well. As DTx emerge in medical, surgical and radiation oncology, further studies are needed to ensure the needs of patients are met with respect to digital literacy and equity. In this review, we will explore these new modalities and the spectrum of possible future benefits.
Keywords: Digital therapeutics, digital health, patient-reported outcomes, quality of life, overall survival, software as a medical device, virtual reality
Digital therapeutics (DTx) are defined by the Digital Therapeutics Alliance as “evidence-based therapeutic interventions driven by high-quality software programs to prevent, manage, or treat a medical disorder or disease” (DTxalliance.org). In short, there are 2 requirements to be considered a DTx. First, it must be software — often categorized as software as a medical device (SaMD). Briefly, hardware refers to physical devices such as phones, computers, tablets or sensors, whereas software refers to a collection of instructions telling hardware what to do. Second, since DTx are designed to offer therapeutic value, they must be approved for use by recognized regulatory agencies such as the Food and Drug Administration (FDA). Digital sensors, wearable devices, virtual reality (VR) systems with therapeutic intent, and artificial intelligence (AI) devices are all examples of DTx.2
For SaMD to enter the public markets, it must either obtain de novo premarket approval (PMA) or qualify for 510(k) clearance. Devices with 510(k) clearance can forgo clinical trials and testing if the device is “substantially equivalent” to something already on the market. For de novo PMA, clinical trials must show adequate safety, efficacy, and be either equivalent or superior to the standard of care. Even after FDA approval, postmarket surveillance must be performed to identify long-term side effects; these roughly translate to phase I, II, III and IV clinical trials, respectively.
In contrast to hardware-based medical devices, SaMD regulation places larger emphasis on the phase IV component, since software is regularly updated. There are enough differences between hardware-based medical devices and SaMD to warrant independent regulatory processes. Appropriately, the FDA started a Software Precertification Pilot Program to “help inform the development of a future regulatory model that will provide more streamlined and efficient regulatory oversight of SaMD developed by manufacturers who have demonstrated a robust culture of quality and organizational excellence, and are committed to monitoring real-world performance of their products once they reach the US market.”3 The 9 companies selected to participate in the Pre-Cert Pilot Program are Apple, Fitbit (Google subsidiary), Verily (Google subsidiary), Johnson & Johnson, Pear Therapeutics, Phosphorus, Roche, Samsung, and Tidepool. This program will attempt to define the regulatory infrastructure for future SaMD approvals, emphasizing the developer’s track record for good manufacturing practices in the setting of software development. This way, instead of trying to anticipate the relative safety and efficacy of eventual software updates to an approved DTx, the due diligence is centered on the developer’s credibility to produce ethical products.
With these definitions, it is important to differentiate DTx from other digital wellness apps that exist in the consumer marketplace. To be considered a DTx, it is essential that high-quality clinical studies support efficacy and the intervention be of a therapeutic nature available either over the counter or prescribed by a physician.4,5 DTx can work alone or in combination with other drugs and active treatment measures.6
Applications in Oncology
In 2016, a Blue Ribbon Panel was established as part of the Cancer Moonshot program to design a roadmap toward exploiting new advances in cancer diagnosis, prevention, and treatment.7 As part of this initiative, attention was focused on the importance of patient-centered care and prioritizing prevention strategies, acknowledging that although therapeutic interventions have improved, many patients will live with their cancers like a chronic disease. In addition, the key lifestyle changes affecting cancer development were highlighted, citing the need for behavioral approaches to control smoking, obesity, and sedentary behavior.
If diet, nutrition, obesity, sedentary behavior, and lack of emotional and social support are contributing to the increasing global rise in cancer, strategies are urgently needed to address these health issues at scale.8 This challenge may provide DTx a potentially transformative role in supporting self-management of chronic conditions that complements conventional cancer screening, monitoring and treatment with the promise of increasing efficiency, improving outcomes and decreasing costs.9 In the US, the population is aging and has been increasingly affected by chronic conditions; indeed, nearly two-thirds of Medicare beneficiaries have 2 or more medical conditions and nearly one-quarter have 4 or more chronic condititions.10,11 In a recent study of over 230,000 Medicare beneficiaries, a third of newly diagnosed cancer patients had concomitant anxiety or depression with higher monthly health care costs ranging from $735 to $1931, depending on when the condition was diagnosed and the tumor type.12 Patients with significant comorbidities during cancer treatment face increases in all-cause mortality as well as treatment-related toxicity.13 During cancer treatment, symptoms are common, potentially leading to functional decline as well as the need for unscheduled visits to the clinic or ER. Conventional systems may not detect clinical changes in advance of acute deterioration, limiting the chances for provider intervention and thus paving the way for potential DTx to bridge the gap.
Currently, the main indications for DTx in oncology have been associated with managing treatment-related symptoms, with significant interest in optimizing digital transfer of patient-reported outcomes (PROs), as well as cognitive behavioral stress management.1 The goals of incorporating DTx into oncology care, explored in recent clinical studies, are improved overall survival and quality of life, fewer acute intervention visits in urgent care centers or hospitalizations, improved adherence to the treatment plan, and more effective ways for patients to manage symptom distress and report their medical symptoms to their care teams (Table 1).1,14 Although current evidence-based studies supporting the integration of DTx into cancer care are limited, the ones that have been completed show potential to improve outcomes. The first step to incorporating a DTx is ensuring that there is adequate patient engagement. Using a 4-week DTx that consisted of food logging, activity tracking, surveys, and receiving educational content to improve quality of life for breast cancer patients through mindfulness, sleep, stress management, and nutrition, data showed that there was high retention, engagement, and acceptability.15 These results were especially encouraging given that most of the patients were actively receiving chemotherapy, radiation therapy or both. In this study, the app collected information such as engagement, retention, step goal attainment, and PROs about energy, stress and quality of sleep. A randomized study is being planned to continue this work.
Another recent study evaluated 766 patients with advanced solid cancers, randomizing them to a DTx intervention for digital symptom monitoring vs conventional symptom monitoring. In the experimental arm, patients self-reported 12 common symptoms from the National Cancer Institute’s Common Terminology Criteria for Adverse Events.16,17 Results showed improved overall survival in the intervention group (31.2 months vs 26.0 months, P = 0.03), significantly less emergency room (ER) visits (34% vs 41%, P = 0.02) as well as improved Health Related Quality of Life (HRQL) (34% vs 18%, P < 0.001). In addition, the DTx intervention group patients were able to remain on chemotherapy longer (8.2 months vs 6.3 months, P = 0.002). Similar improvements in overall survival (OS) have been reported for patients with lung cancer, with those randomized to a DTx intervention having a median OS of 22.4 months vs 16.7 months in the control arm.18
Digital PROs have also been evaluated in the cancer surgery setting, with data showing improved postoperative symptom control;19 in this study, patients underwent thoracotomy for primary or metastatic cancer involving the lung. Following hospital discharge, all patients reported symptoms via automated telephone calls for 4 weeks. The 100 patients included were randomized to a control group
or intervention group, with the intervention consisting of an email alert generated to the clinical team if a subset of symptoms exceeded the threshold for severity. The intervention group experienced a greater reduction in symptom threshold events than controls (19% vs 8%) and a more rapid decline in events. Similar findings have also been reported in the setting of gynecologic cancer, esophageal cancer, colorectal cancer, and liver cancer surgery.20
Although the assessment of electronic patient-reported outcomes (ePROs) is feasible in surgical oncology patients with the opportunity for triggered intervention, there have not yet been any large-scale randomized controlled trials, thus slowing adoption.
Recent data suggest that digital PROs can be applied in large, real-world, population-based studies with similar findings.21 Barbera reported the Canadian experience of inviting cancer patients to report 9 PRO symptoms at kiosks in clinic waiting rooms prior to visits with care teams reviewing the results.22 The patients were matched with a comparison group who did not use PROs, finding an 8% reduction in ER visits and a 14% reduction in hospitalizations. Real-world data also support the integration of DTx into the setting of patients with chronic insomnia, with results from 7216 patients using the intervention outside of a clinical trial reporting 61.4% had a meaningful response.23 Thus, available data suggest significant potential for DTx to improve outcomes both in the prospective clinical trial as well as the real-world setting, suggesting scalability across large cancer patient populations.
Other studies have focused on additional clinically relevant digital measures.24-26 Liu et al reported a positive overall patient experience in those randomized in a digital intervention to manage the acute treatment-related effects of diarrhea and hypertension associated with systemic therapy for ovarian cancer.27 In breast cancer patients, greater increases in stress management skills were reported in the randomized digital intervention group compared with the control group (P < 0.001).28 Finally, investigators have also reported the potential of DTx to decrease fatigue, with Spahrkäs et al reporting greater improvements in fatigue severity and overall quality of life (P < 0.01).29
Pain associated with cancer and its treatment is another promising area of DTx investigation. One recent study of 126 patients evaluated whether a DTx incorporating VR could improve the experience of patients undergoing a bone marrow biopsy.30 The study was a multicenter randomized phase III trial evaluating the VR intervention named Bliss before and during the procedure, exploring this VR DTx for its potential as a distraction therapy. Although the intensity of the pain did not improve in the VR intervention arm, the Bliss relaxation method was well tolerated with high satisfaction of both patients and providers. Early data in the pediatric/adolescent populations also shows hope for improving outcomes, with a pilot randomized trial comparing VR to iPad distraction therapy in 20 patients favoring the VR arm with trends toward less pain and distress.31
Review of VR DTx suggests a range of possible uses, including distraction from painful procedures, chemotherapy, and hospitalization itself.32 In their assessment, Chirico et al reviewed 19 studies that evaluated the efficacy of a VR intervention during chemotherapy, finding that all reported a reduction of patient distress with less anxiety and fatigue as well. In the 3 studies they reviewed where patients were tested during painful procedures, there was significant pain reduction. Finally, the authors evaluated 4 studies that evaluated the effects of a VR intervention on hospitalized patients, finding all studies demonstrated positive effects. Recent data also support integration of VR strategies to improve relaxation in a radiation therapy department for patients, family/friends, and staff.33 At the University of Pennsylvania, 119 subjects were selected to participate in a VR relaxation experience in the waiting room and participate in a follow-up survey. The experience consisted of a natural scenario on a lake with a guided meditation. The satisfaction of this group was positive; 96% enjoyed the experience and 97% would recommend it to others, with the majority (80%) noting more relaxation and (65%) less anxiety.
Additional radiation oncology studies incorporating DTx are beginning to emerge, suggesting significant potential to improve patient outcomes.34-36 Indeed, applications in the setting of protracted multiweek courses of therapy would align well to determine if such interventions could improve well-being during treatment and avoid interval unscheduled medical care such as ER visits and hospitalizations. Data from the SHIELD-RT trial, which incorporated machine learning to identify patients at high risk of unplanned acute care and then randomized to usual care vs twice weekly MD visits, support this approach and reported a significant decrease in acute-care visits during radiation therapy from 22% to 12%.37 With data suggesting that DTx can retain patients receiving chemotherapy on schedule, future studies can also evaluate whether such benefits can be seen in patients receiving radiation therapy to result in fewer treatment interruptions. DTx that address symptom management may be particularly relevant to improve outcomes in patients receiving combined modality therapy. Moreover, with many patients experiencing financial toxicity during treatment,38 DTx may hold promise in improving overall function by decreasing fatigue and stress, thus mitigating the economic cost of time away from work.
In addition, cancer patients may benefit from DTx that can be prescribed to help them manage comorbidities, which can frequently increase the cost of care. This is especially important since nearly 50% of the US population has a chronic disease such as diabetes, heart disease, obesity, hypertension, and chronic respiratory conditions.39 DTx solutions currently exist to improve management of type 2 diabetes, substance use disorder, major depressive disorder and insomnia,4 all of which can complicate the course of cancer care. In addition to comorbidities, medication adherence is a significant issue with estimates that globally, up to 50% of patients do not take their medication as recommended; in the US, the cost of this is estimated to be $289 billion annually.40 DTx solutions being tested range from AI systems using psychological modeling to personalize conversations to foster medication adherence, to digital pills that have sensors that send a record of the ingestion to a mobile app shared with the health care team.41
Some prescription DTx may improve quality of life in oncology patients with comorbid conditions (Table 2). BlueStar RX, Insulia, and dNav are marketed for patients with type 2 diabetes.42-44 These mobile apps are primarily designed to assist patients with insulin titration using AI. Pear Therapeutics produced 2 FDA-approved products directed toward patients with substance use disorder, opioid use disorder, and chronic insomnia.45-47 They function through the ability to deliver cognitive behavioral therapy (CBT) as adjuncts to pharmaceutical therapy. In addition to on-demand therapy delivery, CBT, biofeedback training and medication adjustment AI, remote patient monitoring (RPM) is being heavily explored in oncology. Many of these apps are readily available “over-the-counter” and do not need a prescription. While high-level evidence is lacking, initial feasibility studies have shown promise for RPM solutions such as those designed by Kaiku Health,48 Navigating Cancer,49 and Noona.50
The studies incorporating Noona into the clinical workflow have shown promising results with implications for radiation oncology outpatient clinical workflow. Peltola et al evaluated its integration with 44 cancer patients and 17 health care professionals; 93% of the patients and 88% of the medical professionals reported that the program was easy to use.50 A study of 765 patients with breast cancer randomized to follow up with Noona vs traditional phone calls, changing to the opposite group after 6 months, and then evaluating preferences at 1 year, reporting that 30% of patients favored Noona, 30% traditional phone calls, and an additional 30% noted that both were equally good.51 Takala et al recently described integrating Noona into the clinical workflow of Tays Cancer Centre in Finland with 253 patients with early stage breast cancer.52 More than 82% of patients regularly engaged with the app and 89% of patients were still responding 3 months after radiation therapy treatment concluded. During treatment, 39.3% of patients engaged with the app to report symptoms while 60.7% engaged with treatment-related questions or to ask advice about treatment. Interestingly, anxiety as well as tiredness and pain were reported via Noona far more often than during the in-person visits, suggesting that Noona may transcend some barriers patients face in traditional reporting. In an additional study of 1420 patients, the Noona cancer follow-up application (CFUA) was evaluated along with a traditional callback feature triaged by a digital tool.53 Noona’s CFUA in this study improved the accessibility rate of telephone services such that the same number of nurses was able to manage more contacts in less time and became an accepted part of the workflow so that all nurses used this feature daily or at least weekly. Importantly, the investigators surveyed the nurses and noted that they favored the integration of the digital tools. These findings suggest that future studies are needed to determine the full impact of incorporating these digital tools into routine practice.
As the effectiveness of cancer treatments has improved, there are more global survivors, and more patients dealing with cancer as a chronic disease. Estimates suggest that by 2030, 22.1 million cancer survivors will be living in the US.54 Up to half of all cancer patients at some point in their course will experience anxiety, depression or psychosocial distress55 with evidence that this can especially lower the quality of life of survivors and adversely impact long-term survival.56 As treatments improve and are associated with higher rates of long-term survival, the need for patient compliance and adoption of healthy lifestyle behaviors is especially important given the risks of recurrence and late effects. Indeed, there can be a wide range of side effects with the more complex treatment modalities, such as immunotherapies, which are being increasingly combined with radiation therapy. Whether these combinations may affect patients’ long-term quality of life is not well studied at this time but digital monitoring systems may be useful to track not only acute but also late sequelae.57,58
With respect to chronic pain, DTx hold promise to address the interpretation of pain via a neural systems approach.59 DTx may also soon play a role in management of late effects of cancer therapy, with potential to integrate solutions to treat incontinence.60 No data yet exist on outcomes in cancer patients, but data so far have been encouraging. Weinstein et al reported the results of a single-arm, 10-week prospective pilot trial in women with fecal incontinence, finding there was significant improvement in symptom-specific severity and quality of life using the DTx.61 Karaman et al reported that patients who received treatment with a transcutaneous electrical stimulator had less urinary incontinence than patients who just performed Kegel exercises, suggesting that there may be a role in the oncology setting for patients as well.62
In addition to incontinence, patients can also experience effects of bowel dysfunction after pelvic radiation therapy. Data in the setting of patients with irritable bowel syndrome (IBS) have shown how effective a mobile DTx can be to self-manage symptoms.63 Additional DTx are being piloted that integrate a patient’s genetic and baseline gut microbiome data with results showing effective symptom severity reduction including IBS, diarrhea, and constipation.64
Key Considerations: Practice Incorporation, Access to DTx, Digital Literacy, Digital Equity
Given the changing health care landscape since the adoption of the Affordable Care Act, DTx may emerge to fill gaps to improve quality and patient experience. As noted above, some systems such as Noona are already showing that the clinical experience can be improved while accommodating more patients and the same level of staff. With the Radiation Oncology Alternative Payment Model (RO-APM) in effect as of January 2022, 4 quality measures are being evaluated, some of which could be impacted by DTx: the plan of care for pain, the treatment summary communication, screening for depression and follow-up plan, as well as an advance care plan.65 Since the model looks at a 90-day episode of care, DTx may help evaluate patients during and after treatment. RCM
of pain and VR interventions may hold future promise in relieving pain while additional CBT DTx may help manage depression. With the digital callback features and interactions of many DTx, the patient experience may be improved. More studies are needed to quantify the return on DTx investment in terms of enhancing the patient and staff experience as well as decreasing staffing, increasing efficiency, and even intervening earlier to address disease recurrence or late effects.
Even after identifying a DTx that may benefit a patient, significant barriers must be overcome before implementing the device in mainstream practice. Software developed by for-profit companies have a goal, expectedly, to generate revenue. Ultimately, the most secure revenue line comes from universal commercial insurance coverage. However, many DTx are not universally covered and products such as leva and Nerivio are paid out of pocket, restricting the DTx to patients with resources and potentially exacerbating health inequities. Future methods of reimbursement for DTx may include some form of managed care such as employers, accountable care organizations, and Medicare Advantage health plans.
In addition to financial incentives to the health care system, the end user and provider must be accepting of digital technology. Digital health literacy has been defined as the “capabilities and resources required for individuals to use and benefit from digital health resources.”66 Self-report instruments to measure such competence, such as the Digital Health Literacy Instrument (DHLI), which includes evaluation of operational skills, navigation skills, information searching, reliability, and relevance, have shown significant correlation with age, education, internet use, health-related internet use, health status and health literacy.67
In 2021, 85% of US patients own a smartphone, a number expected to increase with no known saturation point. This statistic does not change by race/ethnicity but does decrease with lower socioeconomic means.68 A disproportionate number of older “baby boomer” patients (born in 1946 to 1964) are digitally illiterate. However, if the user experience is well designed, seamless and automated, the barriers to overcome digital illiteracy may be avoided entirely.66
Another benefit of SaMD is patient-generated health data, but providers must be wary. Although using DTx to passively collect data can generate novel digital biomarkers and insights, as well as improve overall patient care efficiently and effectively, data ownership and stewardship do not yet have the robust regulatory oversight needed.69
While 85% of the US population has a smartphone, the 15% who do not are most likely to benefit from DTx. In the setting of a global pandemic, remote access became increasingly important, yet digital inclusion may be lacking and must be factored in
when developing and incorporating DTx solutions since digital access can be considered a new social determinant of health.70,71 In this age of all things digital and data-driven, thoughtful management and oversight of data is critical to producing meaningful yet relevant results.
One potential area to expand digital inclusion may be with the opportunities within the decentralized clinical trial (DCT) landscape.72 Since only 5% of eligible patients participate in clinical trials, there may be significant improvement with DCTs such that a wider range of patients can enroll secondary to the reduced costs and commitments. Mitigation of economic, geographic, and job disparities may be possible with DCTs and DTx with ePROs may have a prominent role. With this system, it may be possible to recruit digitally from communities that have been historically marginalized from clinical trials. Current infrastructure to foster the wide-spread adoption of DCTs is lacking but with the continued emerging spectrum of DTx, such support may soon arise.
At one of the author’s institutions, incorporating DTx into the clinic workflow required a few “readiness checks.” DTx utility is demographic dependent. Prior to an attempt at introducing DTx into the clinic, each institution’s patient and staff constituency should be evaluated for digital literacy, DTx acceptability, electronic medical record interoperability, and avenues for financial support in the anticipated absence of insurance reimbursements.
Conclusion
DTx is a subdivision of digital health defined by evidence-based software interventions to prevent, manage, or treat a medical disorder or disease. Although formal use of the term dates back to 2012,2 only more recently have studies reported improved outcomes with the integration of DTx into clinical practice. Given the potential for DTx to improve outcomes across the spectrum of cancer care, further data in the oncology setting is eagerly awaited.
References
- Gussoni G, Ravot E, Zecchina M, et al. Digital therapeutics in oncology: findings, barriers and prospects. A narrative review. Ann Res Oncol. 2022;02(01):55. doi:10.48286/aro.2022.39
- Dang A, Arora D, Rane P. Role of digital therapeutics and the changing future of healthcare. J Family Med Prim Care. 2020;9(5):2207-2213. doi:10.4103/jfmpc.jfmpc_105_20
- US Food and Drug Administration. Digital Health Software Precertification (Pre-Cert) Program. FDA. Published March 8, 2022. Accessed April 13, 2022. https://www.fda.gov/medical-devices/digital-health-center-excellence/digital-health-software-precertification-pre-cert-program
- Patel NA, Butte AJ. Characteristics and challenges of the clinical pipeline of digital therapeutics. NPJ Digit Med. 2020;3(1):159. doi:10.1038/s41746-020-00370-8
- Recchia G, Maria Capuano D, Mistri N, Verna R. Digital therapeutics–what they are, what they will be. Act Sci Medic. 2020;4(3):01-09. doi:10.31080/ASMS.2020.04.0575
- Sverdlov O, van Dam J, Hannesdottir K, Thornton-Wells T. Digital therapeutics: an integral component of digital innovation in drug development. Clin Pharmacol Ther. 2018;104(1):72-80. doi:10.1002/cpt.1036
- Jaffee EM, Dang CV, Agus DB, et al. Future cancer research priorities in the USA: a Lancet Oncology Commission. Lancet Oncol. 2017;18(11):e653-e706. doi:10.1016/S1470-2045(17)30698-8
- Kerr J, Anderson C, Lippman SM. Physical activity, sedentary behaviour, diet, and cancer: an update and emerging new evidence. Lancet Oncol. 2017;18(8):e457-e471. doi:10.1016/S1470-2045(17)30411-4
- Sandman K, Vieweg DC, Forsythe A. PNS85 Economic evaluations of digital therapeutics (DTX) from a US perspective. Value Health. 2021;24:S188. doi:10.1016/j.jval.2021.04.939
- Ritchie CS, Kvale E, Fisch MJ. Multimorbidity: an issue of growing importance for oncologists. J Oncol Pract. 2011;7(6):371-374. doi:10.1200/JOP.2011.000460
- Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med. 2002;162(20):2269-2276. doi:10.1001/archinte.162.20.2269
- Birch K, Malecki MJ, MacEwan JP, Chung S. HSR22-131: Incremental health care costs of anxiety and depression among Medicare beneficiaries with cancer. J Nat Comp Cancer Net. 2022;20(3.5):HSR22-131. doi:10.6004/jnccn.2021.7251
- Williams GR, Deal AM, Lund JL, et al. Patient-reported comorbidity and survival in older adults with cancer. Oncologist. 2018;23(4):433-439. doi:10.1634/theoncologist.2017-0404
- Aapro M, Bossi P, Dasari A, et al. Digital health for optimal supportive care in oncology: benefits, limits, and future perspectives. Support Care Cancer. 2020;28(10):4589-4612. doi:10.1007/s00520-020-05539-1
- Thorvardardottir G, Gudmundsson H, Meszaros J, et al. A digital therapeutic intervention for breast cancer patients during active treatment: a feasibility study. Ann Oncol. 2022;33:224-231. doi:10.1016/annonc/annonc895
- 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. 2017;318(2):197-198. doi:10.1001/jama.2017.7156
- 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(6):557-565. doi:10.1200/JCO.2015.63.0830
- Denis F, Yossi S, Septans AL, et al. Improving survival in patients treated for a lung cancer using self-evaluated symptoms reported through a web application. Am J Clin Oncol. 2017;40(5):464-469. doi:10.1097/COC.0000000000000189
- Cleeland CS, Wang XS, Shi Q, et al. Automated symptom alerts reduce postoperative symptom severity after cancer surgery: a randomized controlled clinical trial. J Clin Oncol. 2011;29(8):994-1000. doi:10.1200/JCO.2010.29.8315
- Melstrom L, Rodin A, Rossi L, Fu P, Fong Y, Sun V. Patient generated health data and electronic health record integration in oncologic surgery: a call for artificial intelligence and machine learning. J Surg Oncol. 2020;123. doi:10.1002/jso.26232
- Basch E, Mody GN, Dueck AC. Electronic patient-reported outcomes as digital therapeutics to improve cancer outcomes. JCO Oncol Pract. Published online June 2, 2020. doi:10.1200/OP.20.00264
- 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. 2020;16(9):e958-e965. doi:10.1200/JOP.19.00660
- Ritterband LM, Thorndike FP, Morin CM, et al. Real-world evidence from users of a behavioral digital therapeutic for chronic insomnia. Behav Res Ther. 2022;153:104084. doi:10.1016/j.brat.2022.104084
- Shandhi MMH, Goldsack JC, Ryan K, et al. Recent academic research on clinically relevant digital measures: systematic review. J Med Internet Res. 2021;23(9):e29875. doi:10.2196/29875
- Bakker JP, Goldsack JC, Clarke M, et al. A systematic review of feasibility studies promoting the use of mobile technologies in clinical research. NPJ Digit Med. 2019;2(1):1-7. doi:10.1038/s41746-019-0125-x
- 2Library of Digital Endpoints. Digital Medicine Society (DiMe). Accessed April 12, 2022. https://www.dimesociety.org/communication-education/library-of-digital-endpoints/
- Liu JF, Lee J min, Strock E, et al. Technology applications: use of digital health technology to enable drug development. JCO Clin Cancer Inform. 2018;(2):1-12. doi:10.1200/CCI.17.00153
- Taub CJ, Lippman ME, Hudson BI, et al. The effects of a randomized trial of brief forms of stress management on RAGE-associated S100A8/A9 in patients with breast cancer undergoing primary treatment. Cancer. 2019;125(10):1717-1725. doi:10.1002/cncr.31965
- Spahrkäs SS, Looijmans A, Sanderman R, Hagedoorn M. How does the Untire app alleviate cancer-related fatigue? A longitudinal mediation analysis. Psycho-Oncology. 2022;31(6). doi:10.1002/pon.5886
- Le Du K, Septans AL, Maloisel F, et al. A new option in pain prevention with bliss, a therapeutic virtual reality solution in bone marrow biopsy context: results of a French open-label multicenter randomized phase II/III study (REVEH Trial). J Clin Oncol. 2021;39(15_suppl):6573-6573. doi:10.1200/JCO.2021.39.15_suppl.6573
- Hundert AS, Birnie KA, Abla O, et al. A pilot randomized controlled trial of virtual reality distraction to reduce procedural pain during subcutaneous port access in children and adolescents with cancer. Clin J Pain. 2022;38(3):189-196. doi:10.1097/AJP.0000000000001017
- Chirico A, Lucidi F, De Laurentiis M, Milanese C, Napoli A, Giordano A. Virtual reality in health system: beyond entertainment. A mini-review on the efficacy of VR during cancer treatment. J Cell Physiol. 2016;231(2):275-287. doi:10.1002/jcp.25117
- Amaniera I, Nibquer-Cohen F, Levin W, Metz J. First report of the integration of virtual reality relaxation in a radiation therapy department. Int J Radiat Oncol. 2020;108(2). doi:10.1016/j.ijrobp.2020.02.491
- Yang DX, Thea J, An Y, Yu JB. Digital health application for real-time patient-reported outcomes during prostate radiotherapy. J Clin Oncol. 2016;34(2_suppl):157-157. doi:10.1200/jco.2016.34.2_suppl.157
- Møller PK, Pappot H, Bernchou U, et al. Feasibility, usability and acceptance of weekly electronic patient-reported outcomes among patients receiving pelvic CT- or online MR-guided radiotherapy – a prospective pilot study. Tech Innovat Pat Supp Radiat Oncol. 2022;21:8-15. doi:10.1016/j.tipsro.2021.12.001
- Böhner AMC, Schmeel LC, Andreas F, et al. How to PROceed? Reviewing obstacles and perspectives in patient-centered digital care in radiation oncology. J Radiat Oncol Inform. 2021;11(1):6-6. doi:10.5166/jroi.11.1.1
- Hong JC, Eclov NCW, Dalal NH, et al. System for High-intensity evaluation during radiation therapy (SHIELD-RT): a prospective randomized study of machine learning-directed clinical evaluations during radiation and chemoradiation. J Clin Oncol. 2020;38(31):3652-3661. doi:10.1200/JCO.20.01688
- Lentz R, Benson AB, Kircher S. Financial toxicity in cancer care: prevalence, causes, consequences, and reduction strategies. J Surg Oncol. 2019;120(1):85-92. doi:10.1002/jso.25374
- Kvedar JC, Fogel AL, Elenko E, Zohar D. Digital medicine’s march on chronic disease. Nat Biotechnol. 2016;34(3):239-246. doi:10.1038/nbt.3495
- Makin S. The emerging world of digital therapeutics. Nature. 2019;573(7775):S106-S109. doi:10.1038/d41586-019-02873-1
- Hafezi H, Robertson TL, Moon GD, Au-Yeung KY, Zdeblick MJ, Savage GM. An ingestible sensor for measuring medication adherence. IEEE Trans Biomed Eng. 2015;62(1):99-109. doi:10.1109/TBME.2014.2341272
- Quinn CC, Clough SS, Minor JM, Lender D, Okafor MC, Gruber-Baldini A. WellDoc mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. Diabetes Technol Ther. 2008;10(3):160-168. doi:10.1089/dia.2008.0283
- Franc S, Joubert M, Daoudi A, et al. Efficacy of two telemonitoring systems to improve glycaemic control during basal insulin initiation in patients with type 2 diabetes: The TeleDiab-2 randomized controlled trial. Diabetes Obes Metab. 2019;21(10):2327-2332. doi:10.1111/dom.13806
- Bergenstal RM, Johnson M, Passi R, et al. Automated insulin dosing guidance to optimise insulin management in patients with type 2 diabetes: a multicentre, randomised controlled trial. Lancet. 2019;393(10176):1138-1148. doi:10.1016/S0140-6736(19)30368-X
- Campbell ANC, Nunes EV, Matthews AG, et al. Internet-delivered treatment for substance abuse: a multisite randomized controlled trial. Am J Psychiatry. 2014;171(6):683-690. doi:10.1176/appi.ajp.2014.13081055
- Christensen DR, Landes RD, Jackson L, et al. Adding an Internet-delivered treatment to an efficacious treatment package for opioid dependence. J Consult Clin Psychol. 2014;82(6):964-972. doi:10.1037/a0037496
- Ritterband LM, Thorndike FP, Ingersoll KS, et al. Effect of a web-based cognitive behavior therapy for insomnia intervention with 1-year follow-up: a randomized clinical trial. JAMA Psychiatry. 2017;74(1):68-75. doi:10.1001/jamapsychiatry.2016.3249
- Iivanainen S, Alanko T, Vihinen P, et al. Follow-up of cancer patients receiving anti-PD-(L)1 therapy using an electronic patient-reported outcomes tool (KISS): prospective feasibility cohort study. JMIR Form Res. 2020;4(10):e17898. doi:10.2196/17898
- Patt D, Wilfong L, Hudson KE, et al. Implementation of electronic patient-reported outcomes for symptom monitoring in a large multisite community oncology practice: dancing the Texas two-step through a pandemic. JCO Clin Cancer Inform. 2021;5:615-621. doi:10.1200/CCI.21.00063
- Peltola MK, Poikonen-Saksela P, Mattson J, Parkkari T. A novel digital patient-reported outcome platform (Noona) for clinical use in patients with cancer: pilot study assessing suitability. JMIR Form Res. 2021;5(5):e16156. doi:10.2196/16156
- Mattson J, Peltola M, Poikonen-Saksela P, et al. Follow-up of early breast cancer (BC) patients by telephone or mobile software. JCO. 2018;36(15_suppl):e18883-e18883. doi:10.1200/JCO.2018.36.15_suppl.e18883
- Takala L, Kuusinen TE, Skyttä T, Kellokumpu-Lehtinen PL, Bärlund M. Electronic patient-reported outcomes during breast cancer adjuvant radiotherapy. Clin Breast Cancer. 2020;21(3):e252-e270. doi:10.1016/j.clbc.2020.10.004
- Bärlund M, Takala L, Tiainen L, Kellokumpu-Lehtinen PL. Real-world evidence of implementing eHealth enables fluent symptom-based follow-up of a growing number of patients with breast cancer with the same healthcare resources. Clin Breast Cancer. 2022;22(3):261-268. doi:10.1016/j.clbc.2021.09.005
- American Cancer Society. Cancer Facts & Figures 2019. Atlanta: American Cancer Society; 2019.
- Mehnert A, Hartung TJ, Friedrich M, et al. One in two cancer patients is significantly distressed: prevalence and indicators of distress. Psychooncology. 2018;27(1):75-82. doi:10.1002/pon.4464
Citation
Jin W, Mohan S, Adams M, Hoffe S, Robinson E. The Emerging Role of Digital Therapeutics in Medical, Surgical and Radiation Oncology. Appl Radiat Oncol. 2022;(2):10-18.
July 15, 2022