Evidence map›Paper›PMID 28521456›Full record

ArticleOncology letters2017

The association of p53 expression levels with clinicopathological features and prognosis of patients with colon cancer following surgery.

Da-Zhong Cao, Xi-Long Ou, Ting Yu

Abstract read
In one paragraph

Article in Oncology letters, 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
–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

5 citing papers in PubMed.

  1. Article
  2. The p53 Pathway Related Genes Predict the Prognosis of Colon Cancer.International journal of general medicine · 2022
    Article
  3. Article
  4. Article
  5. 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

3 authors.

Da-Zhong CaoDepartment of Gastroenterology, The Affiliated ZhongDa Hospital of Southeast University, Nanjing, Jiangsu 210009, P.R. China.
Xi-Long OuDepartment of Gastroenterology, The Affiliated ZhongDa Hospital of Southeast University, Nanjing, Jiangsu 210009, P.R. China.
Ting YuDepartment of Gastroenterology, The Affiliated ZhongDa Hospital of Southeast University, Nanjing, Jiangsu 210009, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to examine the association of p53 expression levels with clinicopathological features and prognosis of patients with colon cancer following surgery. The present study included 484 patients with colon cancer that underwent colon resection between December 2003 and December 2011. All follow-ups were censored in December 2013 with a median follow-up time of 43 months. Kaplan-Meier survival curves and Cox regression analysis were used to determine predictors for overall survival rate. p53 expression status (positive or negative) was significantly different between patient groups when categorized by age distribution, disease course, tumor location, maximum tumor diameter, depth of tumor invasion, Dukes' stage, distant metastasis and lymph node (LN) metastasis (P<0.05). Cox regression analysis revealed that age, surgery type, histological subtypes, tumor size, tumor location, LN metastasis, distant metastases, Dukes' stage and p53 expression status are independent factors influencing the survival rate of patients with colon cancer following surgery (P<0.05). Therefore, the present study revealed that the loss of p53 expression levels in tumors was associated with aggressive clinicopathological characteristics in patients with colon cancer.

Indexed as

clinicopathological featurescolon cancercolorectal cancerCox regression analysisindependent factorsKaplan-Meier methodoverall survival ratep53 expression

Identifiers

PMID28521456
PMCPMC5431169

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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.