Evidence map›Paper›PMID 34912715›Full record

ReviewFrontiers in oncology2021

Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field.

Huzaifa Piperdi, Daniella Portal, Shane S Neibart, Ning J Yue, Salma K Jabbour, Meral Reyhan

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
6.6field-weighted citation impact, top 2% of its field
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

29 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Monitoring lung tumour volume on daily cone beam CT; is it achievable in a real-world setting?Technical innovations & patient support in radiation oncology · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Review
  17. Factors that Influence the Need to Start Adaptive Radiotherapy.Journal of immunotherapy and precision oncology · 2024
    Article
  18. Article
  19. Article
  20. Article
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

6 authors at 3 institutions in 1 country.

Huzaifa PiperdiDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States.
Daniella PortalRutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States.
Shane S NeibartRutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States.
Ning J YueDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States.
Salma K JabbourDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States.
Meral ReyhanDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States.
Rutgers, The State University of New Jersey · USRutgers Cancer Institute of New JerseyState of New Jersey

Funding

Dr. Salma Jabbour’s NCI Research Specialist (Clinician Scientist) Award (R50)R50CA275877 · NCI · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI Salma Jabbour · 2023 to 2026
$785k
NCI NIH HHS R50 CA275877
6 · The paper itself

Abstract

Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.

Indexed as

adaptive planningadaptive radiation therapy (ART)lung cancernon-small cell lung cancersmall cell lung cancer (SCLC)

Identifiers

PMID34912715
PMCPMC8666420
OpenAlexW3217732711

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.