Evidence map›Paper›PMID 29538699›Full record

ArticleJournal of radiation research2018

Assessing the uncertainty in a normal tissue complication probability difference (∆NTCP): radiation-induced liver disease (RILD) in liver tumour patients treated with proton vs X-ray therapy.

Keiji Kobashi, Anussara Prayongrat, Takuya Kimoto, Chie Toramatsu, Yasuhiro Dekura, Norio Katoh, Shinichi Shimizu, Yoichi M Ito, Hiroki Shirato

Open access · goldAbstract readComparative Study
In one paragraph

Article in Journal of radiation research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. NRG Oncology White Paper on the Relative Biological Effectiveness in Proton Therapy.International journal of radiation oncology, biology, physics · 2025
    Review
  4. Article
  5. Roadmap: proton therapy physics and biology.Physics in medicine and biology · 2021
    Review
  6. 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 at 4 institutions in 1 country.

Keiji KobashiDepartment of Medical Physics, Hokkaido University Hospital, North-15 West-7, Kita-ku, Sapporo, 0608638, Japan.
Anussara PrayongratDepartment of Radiation Oncology, Graduate School of Medicine, Hokkaido University, North-15 West-7, Kita-ku, Sapporo, 0608638, Japan.
Takuya KimotoDepartment of Radiology, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, 6028566, Japan.
Chie ToramatsuDepartment of Radiation Oncology, Tokyo Women's Medical University, 8-1,Kawada-cho,Sinjuku,Tokyo, 1628666, Japan.
Yasuhiro DekuraDepartment of Radiation Oncology, Graduate School of Medicine, Hokkaido University, North-15 West-7, Kita-ku, Sapporo, 0608638, Japan.
Norio KatohDepartment of Radiation Oncology, Hokkaido University Hospital, North-15 West-7, Kita-ku, Sapporo, 0608638, Japan.
Shinichi ShimizuDepartment of Radiation Oncology, Faculty of Medicine, Hokkaido University, North-15 West-7, Kita-ku, Sapporo, 0608638, Japan.
Yoichi M ItoDepartment of Biostatistics, Faculty of Medicine, Hokkaido University, North-15 West-7, Kita-ku, Sapporo, 0608638, Japan.
Hiroki ShiratoGlobal Station for Quantum Biomedical Science and Engineering, Global Institute for Cooperative Research and Education, Hokkaido University, North-15 West-7, Kita-ku, Sapporo, 0608638, Japan.
Hokkaido University · JPHokkaido University Hospital · JPKyoto Prefectural University of Medicine · JPTokyo Women's Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern radiotherapy technologies such as proton beam therapy (PBT) permit dose escalation to the tumour and minimize unnecessary doses to normal tissues. To achieve appropriate patient selection for PBT, a normal tissue complication probability (NTCP) model can be applied to estimate the risk of treatment-related toxicity relative to X-ray therapy (XRT). A methodology for estimating the difference in NTCP (∆NTCP), including its uncertainty as a function of dose to normal tissue, is described in this study using the Delta method, a statistical method for evaluating the variance of functions, considering the variance-covariance matrix. We used a virtual individual patient dataset of radiation-induced liver disease (RILD) in liver tumour patients who were treated with XRT as a study model. As an alternative option for individual patient data, dose-bin data, which consists of the number of patients who developed toxicity in each dose level/bin and the total number of patients in that dose level/bin, are useful for multi-institutional data sharing. It provides comparable accuracy with individual patient data when using the Delta method. With reliable NTCP models, the ∆NTCP with uncertainty might potentially guide the use of PBT; however, clinical validation and a cost-effectiveness study are needed to determine the appropriate ∆NTCP threshold.

Indexed as

ProbabilityUncertaintyX-Ray TherapyAlgorithmsHumansLiverLiver NeoplasmsProton TherapyRadiation Injuries

Identifiers

PMID29538699
PMCPMC5868200
OpenAlexW2792929646

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.