Evidence map›Paper›PMID 27460585›Full record

ArticleRadiation oncology (London, England)2016

Methodology for analysis and reporting patterns of failure in the Era of IMRT: head and neck cancer applications.

Abdallah S R Mohamed, David I Rosenthal, Musaddiq J Awan, Adam S Garden, Esengul Kocak-Uzel, Abdelaziz M Belal, Ahmed G El-Gowily, Jack Phan, Beth M Beadle, G Brandon Gunn and 1 more

Abstract read
In one paragraph

Article in Radiation oncology (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Mapping Local Failure Following Bladder Radiotherapy According to Dose.Clinical oncology (Royal College of Radiologists (Great Britain)) · 2022
    Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Patterns of loco-regional progression and patient outcomes after definitive-dose radiation therapy for anaplastic thyroid cancer.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Combining Tumor Segmentation Masks with PET/CT Images and Clinical Data in a Deep Learning Framework for Improved Prognostic Prediction in Head and Neck Squamous Cell Carcinoma.Head and neck tumor segmentation and outcome prediction : second challenge, HECKTOR 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings. Head and Neck Tumor Segmentation Challenge (2nd : 2021 ... · 2022
    Article
  17. Proton Therapy for Major Salivary Gland Cancer: Clinical Outcomes.International journal of particle therapy · 2021
    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

11 authors.

Abdallah S R MohamedHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA. asmohamed@mdanderson.org.
David I RosenthalHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
Musaddiq J AwanDepartment of Radiation Oncology, Case Western Reserve University, Cleveland, OH, USA.
Adam S GardenHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
Esengul Kocak-UzelHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
Abdelaziz M BelalDepartment of Clinical Oncology and nuclear medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt.
Ahmed G El-GowilyDepartment of Clinical Oncology and nuclear medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt.
Jack PhanHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
Beth M BeadleHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
G Brandon GunnHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
Clifton D FullerHead and Neck Section, Division of Radiation Oncology, Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Box 0097, 1515 Holcombe Blvd, Houston, TX, 77030, USA. cdfuller@mdanderson.org.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Paul Calabresi Clinical Oncology AwardK12CA088084 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI David S. Hong, Scott Kopetz · 2000 to 2026
$14.0M
NCI NIH HHS K12 CA088084NCI NIH HHS L30 CA136381NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

backgroundThe aim of this study is to develop a methodology to standardize the analysis and reporting of the patterns of loco-regional failure after IMRT of head and neck cancer. MATERIAL AND

methodsTwenty-one patients with evidence of local and/or regional failure following IMRT for head-and-neck cancer were retrospectively reviewed under approved IRB protocol. Manually delineated recurrent gross disease (rGTV) on the diagnostic CT documenting recurrence (rCT) was co-registered with the original planning CT (pCT) using both deformable (DIR) and rigid (RIR) image registration software. Subsequently, mapped rGTVs were compared relative to original planning target volumes (TVs) and dose using a centroid-based approaches. Failures were then classified into five types based on combined spatial and dosimetric criteria; A (central high dose), B (peripheral high dose), C (central elective dose), D (peripheral elective dose), and E (extraneous dose).

resultsA total of 26 recurrences were identified. Using DIR, recurrences were assigned to more central TVs compared to RIR as detected using the spatial centroid-based method (p = 0.0002). rGTVs mapped using DIR had statistically significant higher mean doses when compared to rGTVs mapped rigidly (mean dose 70 vs. 69 Gy, p = 0.03). According to the proposed classification 22 out of 26 failures were of type A (central high dose) as assessed by DIR method compared to 18 out of 26 for the RIR because of the tendencey of RIR to assign failures more peripherally.

conclusionsRIR tends to assigns failures more peripherally. DIR-based methods showed that the vast majority of failures originated in the high dose target volumes and received full prescribed doses suggesting biological rather than technology-related causes of failure. Validated DIR-based registration is recommended for accurate failure characterization and a novel typology-indicative taxonomy is recommended for failure reporting in the IMRT era.

Indexed as

AdultAgedCarcinoma, Squamous CellFemaleHead and Neck NeoplasmsHumansImage Interpretation, Computer-AssistedMaleMiddle AgedNeoplasm Recurrence, LocalRadiation OncologyRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedResearch DesignRetrospective StudiesSquamous Cell Carcinoma of Head and NeckDeformable image registrationHead-and-neck cancerIMRTPatterns of failure

Identifiers

PMID27460585
PMCPMC4962405

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.