Evidence map›Paper›PMID 38607626›Full record

ArticleJAMA network open2024

Remote Monitoring and Data Collection for Decentralized Clinical Trials.

Bobby Daly, Otis W Brawley, Mary K Gospodarowicz, Olufunmilayo I Olopade, Lola Fashoyin-Aje, Victoria Wolodzko Smart, I-Fen Chang, Craig L Tendler, Geoffrey Kim, Charles S Fuchs and 14 more

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Focused ultrasound for brain metastases.Neuro-oncology advances · 2026
    Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Adoption of Decentralized Trial Elements in Cancer Clinical Trials Supporting FDA Approvals during COVID-19.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Bobby DalyDepartment of Medicine, Memorial Sloan Kettering Cancer Center and Weill Cornell Medicine, New York, New York.
Otis W BrawleySchool of Medicine, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Mary K GospodarowiczPrincess Margaret Cancer Center, University of Toronto, Toronto, Ontario, Canada.
Olufunmilayo I OlopadeMedicine and Human Genetics, Center for Clinical Cancer Genetics and Global Health, University of Chicago Medical Center, Chicago, Illinois.
Lola Fashoyin-AjeOncology Center of Excellence, US Food and Drug Administration, Silver Spring, Maryland.
Victoria Wolodzko SmartSusan G. Komen Foundation, Dallas, Texas.
I-Fen ChangAmgen Inc, Thousand Oaks, California.
Craig L TendlerJanssen, Johnson & Johnson, New Brunswick, New Jersey.
Geoffrey KimBeiGene, Cambridge, Massachusetts.
Charles S FuchsGenentech, South San Francisco, California.
Muhammad Shaalan BegScience 37, Durham, North Carolina.
Lianshan ZhangJiangsu Hengrui Pharmaceuticals, Shanghai, China.
Jeffrey J LegosNovartis, Basel, Switzerland.
Cristina Ortega DuranAstraZeneca, Cambridge, United Kingdom.
Chitkala KalidasBayer, Leverkusen, Germany.
Jing QianAsia Society, New York, New York.
Justin FinneganBloomberg New Economy, Bloomberg LP, New York, New York.
Piotr PilarskiMcKinsey Cancer Center, McKinsey & Company, New York, New York.
Harriet KeaneMcKinsey Cancer Center, McKinsey & Company, New York, New York.
Johanna ShenMcKinsey Cancer Center, McKinsey & Company, New York, New York.
Amy SilversteinMcKinsey Cancer Center, McKinsey & Company, New York, New York.
Yi-Long WuGuangdong Lung Cancer Institute, Chinese Thoracic Oncology Group, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Richard PazdurOncology Center of Excellence, US Food and Drug Administration, Silver Spring, Maryland.
Bob T LiDepartment of Medicine, Memorial Sloan Kettering Cancer Center and Weill Cornell Medicine, New York, New York.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Importance: Less than 5% of patients with cancer enroll in a clinical trial, partly due to financial and logistic burdens, especially among underserved populations. The COVID-19 pandemic marked a substantial shift in the adoption of decentralized trial operations by pharmaceutical companies. Objective: To assess the current global state of adoption of decentralized trial technologies, understand factors that may be driving or preventing adoption, and highlight aspirations and direction for industry to enable more patient-centric trials. Design, Setting, and Participants: The Bloomberg New Economy International Cancer Coalition, composed of patient advocacy, industry, government regulator, and academic medical center representatives, developed a survey directed to global biopharmaceutical companies of the coalition from October 1 through December 31, 2022, with a focus on registrational clinical trials. The data for this survey study were analyzed between January 1 and 31, 2023. Exposure: Adoption of decentralized clinical trial technologies. Main Outcomes and Measures: The survey measured (1) outcomes of different remote monitoring and data collection technologies on patient centricity, (2) adoption of these technologies in oncology and all therapeutic areas, and (3) barriers and facilitators to adoption using descriptive statistics. Results: All 8 invited coalition companies completed the survey, representing 33% of the oncology market by revenues in 2021. Across nearly all technologies, adoption in oncology trials lags that of all trials. In the current state, electronic diaries and electronic clinical outcome assessments are the most used technology, with a mean (SD) of 56% (19%) and 51% (29%) adoption for all trials and oncology trials, respectively, whereas visits within local physician networks is the least adopted at a mean (SD) of 12% (18%) and 7% (9%), respectively. Looking forward, the difference between the current and aspired adoption rate in 5 years for oncology is large, with respondents expecting a 40% or greater absolute adoption increase in 8 of the 11 technologies surveyed. Furthermore, digitally enabled recruitment, local imaging capabilities, and local physician networks were identified as technologies that could be most effective for improving patient centricity in the long term. Conclusions and Relevance: These findings may help to galvanize momentum toward greater adoption of enabling technologies to support a new paradigm of trials that are more accessible, less burdensome, and more inclusive.

Indexed as

Clinical Trials as TopicNeoplasmsData CollectionHumansMedical Oncology

Identifiers

PMID38607626
PMCPMC11015350

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.