Evidence map›Paper›PMID 29228760›Full record

ArticleOncotarget2017

Development and validation of a prognostic nomogram for colorectal cancer after radical resection based on individual patient data from three large-scale phase III trials.

Michitaka Honda, Koji Oba, Takashi Akiyoshi, Hiromichi Maeda, Kosuke Kashiwabara, Mitsuro Kanda, Shuhei Mayanagi, Toru Aoyama, Chikuma Hamada, Sotaro Sadahiro and 5 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

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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

15 authors at 11 institutions in 1 country.

Michitaka Honda *Department of Minimally Invasive Surgical and Medical Oncology, Fukushima Medical University, Fukushima, Japan.
Koji Oba *Department of Biostatistics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Takashi AkiyoshiDepartment of Gastroenterological Surgery, Gastroenterological Center, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Hiromichi MaedaCancer Treatment Center, Kochi Medical School Hospital, Kochi University, Nankoku, Japan.
Kosuke KashiwabaraDepartment of Biostatistics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Mitsuro KandaDepartment of Gastroenterological Surgery (Surgery II), Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shuhei MayanagiDepartment of Surgery, Keio University, Tokyo, Japan.
Toru AoyamaDepartment of Surgery, Yokohama City University, Yokohama, Japan.
Chikuma HamadaFaculty of Engineering, Tokyo University of Science, Tokyo, Japan.
Sotaro SadahiroDepartment of Surgery, Tokai University, Isehara, Japan.
Yosuke FukunagaDepartment of Gastroenterological Surgery, Gastroenterological Center, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Masashi UenoDepartment of Gastroenterological Surgery, Gastroenterological Center, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Junichi SakamotoTokai Central Hospital, Kakamigahara, Japan.
Shigetoyo SajiJapanese Foundation for Multidisciplinary Treatment of Cancer, Tokyo, Japan.
Takaki YoshikawaDepartment of Gastrointestinal Surgery, Kanagawa Cancer Center, Yokohama, Japan.
Japanese Foundation For Cancer Research · JPJapanese Foundation for Multidisciplinary Treatment of Cancer · JPThe University of Tokyo · JPFukushima Medical University · JPKanagawa Cancer CenterKeio University · JPKōchi University · JPNagoya University · JPTokai University · JPTokyo University of Science · JPYokohama City University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew prediction models have so far been developed and assessed for the prognosis of patients who undergo curative resection for colorectal cancer (CRC). MATERIALS AND

methodsWe prepared a clinical dataset including 5,530 patients who participated in three major randomized controlled trials as a training dataset and 2,263 consecutive patients who were treated at a cancer-specialized hospital as a validation dataset. All subjects underwent radical resection for CRC which was histologically diagnosed to be adenocarcinoma. The main outcomes that were predicted were the overall survival (OS) and disease free survival (DFS). The identification of the variables in this nomogram was based on a Cox regression analysis and the model performance was evaluated by Harrell's c-index. The calibration plot and its slope were also studied. For the external validation assessment, risk group stratification was employed.

resultsThe multivariate Cox model identified variables; sex, age, pathological T and N factor, tumor location, size, lymphnode dissection, postoperative complications and adjuvant chemotherapy. The c-index was 0.72 (95% confidence interval [CI] 0.66-0.77) for the OS and 0.74 (95% CI 0.69-0.78) for the DFS. The proposed stratification in the risk groups demonstrated a significant distinction between the Kaplan-Meier curves for OS and DFS in the external validation dataset.

conclusionsWe established a clinically reliable nomogram to predict the OS and DFS in patients with CRC using large scale and reliable independent patient data from phase III randomized controlled trials. The external validity was also confirmed on the practical dataset.

Indexed as

colorectal cancerdisease free survivaloverall survivalprediction modelprognostic nomogram

Identifiers

PMID29228760
PMCPMC5716800
OpenAlexW2766706189

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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.