Evidence map›Paper›PMID 38047220›Full record

ArticleAdvances in radiation oncology

Simulating the Potential of Model-Based Individualized Prescriptions for Ultracentral Lung Tumors.

Ishita Chen, Aditi Iyer, Maria Thor, Abraham J Wu, Aditya Apte, Andreas Rimner, Daniel Gomez, Joseph O Deasy, Andrew Jackson

Abstract read
In one paragraph

Article in Advances in radiation oncology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

9 authors.

Ishita ChenDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
Aditi IyerDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
Maria ThorDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
Abraham J WuDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
Aditya ApteDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
Andreas RimnerDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
Daniel GomezDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
Joseph O DeasyDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
Andrew JacksonDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Dose-distribution radiomics to predict morbidity risk in radiotherapyR01CA198121 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI DEASY, JOSEPH O · 2016 to 2019
$2.3M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA198121
6 · The paper itself

Abstract

Purpose: The use of stereotactic body radiation therapy for ultracentral lung tumors is limited by increased toxicity. We hypothesized that using published normal tissue complication probability (NTCP) and tumor control probability (TCP) models could improve the therapeutic ratio between tumor control and toxicity. A proposed model-based approach was applied to virtually replan early-stage non-small cell lung cancer (NSCLC) tumors. Methods and Materials: The analysis included 63 patients with ultracentral NSCLC tumors treated at our center between 2008 and 2017. Along with current clinical constraints, additional NTCP model-based criteria, including for grade 3+ radiation pneumonitis (RP3+) and grade 2+ esophagitis, were implemented using 4 different fractionation schemes. Scaled dose distributions resulting in the highest TCP without violating constraints were selected (optimal plan [Plan Results: The observed 2-year local control rate was 72% (95% CI, 57%-88%) compared with 87% (range, 6%-93%) for Plan Conclusions: We demonstrated the potential for model-based prescriptions to yield higher TCP while respecting NTCP for patients with ultracentral NSCLC. Individualizing treatments based on NTCP- and TCP-driven simulations halved the predicted relative to the observed rates of RP3+. Our simulations also identified patients whose TCP could not be improved without violating NTCP due to larger tumors or a near tumor to esophagus proximity.

Identifiers

PMID38047220
PMCPMC10692285

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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.