Evidence map›Paper›PMID 34249711›Full record

ArticleFrontiers in oncology2021

Influence of Different Age Cutoff Points on the Prediction of Prognosis of Cancer Patients Receiving ICIs and Potential Mechanistic Exploration.

Rui Guan, Qiong Lyu, Anqi Lin, Junyi Liang, Weimin Ding, Manming Cao, Peng Luo, Jian Zhang

Abstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. PD-1 and PD-L1 expression in rare lung tumors.Pathology oncology research : POR · 2023
    Article
  8. Article
  9. Review
  10. 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

8 authors.

Rui GuanDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Qiong LyuDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Anqi LinDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Junyi LiangDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Weimin DingDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Manming CaoDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Peng LuoDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Jian ZhangDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Age is a potential predictive marker for the prognosis of cancer patients treated with immune checkpoint inhibitors (ICIs), but the appropriate age cutoff point is still controversial. We aimed to explore the influence of different age cutoff points on the prediction of prognosis for patients receiving ICIs and explore the mechanism underlying the appropriate age cutoff point from the aspects of gene mutation and expression, immune cell infiltration and so on. We applied cutoff points of 50, 55, 60, 65, 70, and 75 years old to divide 1660 patients from the Memorial Sloan-Kettering Cancer Center (MSKCC) immunotherapy cohort into older and younger groups and performed survival analysis of the six subgroups. The results showed that older patients had better survival than younger patients in accordance with the cutoff point of 50 years old [median overall survival (OS) (95% CI): 13.0 (10.5-15.5) months

Indexed as

ageICIpan-cancerpredictive markersprognosis

Identifiers

PMID34249711
PMCPMC8260982

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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.