Evidence map›Paper›PMID 34733911›Full record

ArticleAnnals of translational medicine2021

Evaluation of nodal status in intrahepatic cholangiocarcinoma: a population-based study.

Xiaoyuan Chen, Dawei Rong, Long Zhang, Chuangye Ni, Guoyong Han, Yiwei Lu, Xuejiao Chen, Yun Gao, Xuehao Wang

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

13 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Clinical Features and Prognostic Models in Patients with Intrahepatic Cholangiocarcinoma: a Population-Based Analysis.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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.

Xiaoyuan ChenSchool of Medicine, Southeast University, Nanjing, China.
Dawei RongSchool of Medicine, Southeast University, Nanjing, China.
Long ZhangHepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Chuangye NiHepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Guoyong HanHepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yiwei LuHepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Xuejiao ChenHepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yun GaoHepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Xuehao WangSchool of Medicine, Southeast University, Nanjing, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNNanjing Medical University · CNJiangsu Province Hospital · CNSoutheast University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLymph node metastasis (LNM) is a well-established prognostic factor for intrahepatic cholangiocarcinoma (ICC), but there are still some controversies relating to the evaluation of nodal status. Therefore, we investigated the role of lymph node dissection (LND), compared the prognostic performances of different nodal staging systems, and then developed and validated a nomogram to predict cancer-specific survival (CSS) of ICC patients.

methodsThe study cohort was taken from the Surveillance, Epidemiology, and End Results database. Akaike information criterion, Bayesian information criterion, Harrell's C-index and area under the receiver operating characteristic curves were calculated to evaluate the different staging models. The nomogram for the CSS was constructed based on Cox regression models and validated by calibration curves. Decision curve analysis was introduced to examine the clinical value of the models.

resultsA total of 664 patients were enrolled, and 331 (51.4%) patients underwent LND. An increasing number of lymph nodes retrieved showed no oncologic benefit (P=0.876). LNM was identified in 103 (31.1%) patients, which was the cause of their poor prognoses (5-yr CSS 13.1% versus 44.9%, P<0.001). Patients without LNM could not benefit from adjuvant therapy after propensity score matching (P=0.140). Based on the Youden index, 4 or more lymph nodes retrieved might be adequate for accurate staging. The lymph node ratio (LNR) classification, with an optimal cut-off value of 0.15, displayed the best prognostic performance. Age, size, tumor number, T Stage, grade and the LNR classification were independent predictive factors for the CSS in ICC patients. The nomogram for predicting the CSS of ICC patients according to the independent factors was well calibrated and it showed better discrimination power and higher net benefits than the American Joint Committee on Cancer (8th edition) staging system.

conclusionsLNM is an independent prognostic factor in ICC. Although it shows no oncologic benefits, LND should still be considered as a method of stratifying patients, with 4 or more lymph nodes retrieved potentially enough to do so. LNR appears to be a promising and easy-to-use prognosticator for nodal staging. The constructed nomogram could serve as an effective tool to predict the CSS probabilities of ICC patients.

Indexed as

Intrahepatic cholangiocarcinoma (ICC)lymph node dissection (LND)lymph node ratio (LNR)nomogramSurveillance, Epidemiology, and End Results program (SEER program)

Identifiers

PMID34733911
PMCPMC8506549
OpenAlexW3191615900

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.