Evidence map›Paper›PMID 32982441›Full record

ArticleCancer management and research2020

Prognostic Role of Prothrombin Time Activity, Prothrombin Time, Albumin/Globulin Ratio, Platelets, Sex, and Fibrinogen in Predicting Recurrence-Free Survival Time of Renal Cancer.

Zichen Bian, Jialin Meng, Qingsong Niu, Xiaoyan Jin, Jinian Wang, Xingliang Feng, Hong Che, Jun Zhou, Li Zhang, Meng Zhang and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer management and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
1.3field-weighted citation impact, top 17% 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 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

11 authors at 3 institutions in 1 country.

Zichen Bian *Department of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Jialin Meng *Department of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Qingsong NiuDepartment of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Xiaoyan JinThe Second Clinical College of Anhui Medical University, Hefei, Anhui, People's Republic of China.
Jinian WangClinical Skills Training Center, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui, People's Republic of China.
Xingliang FengDepartment of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Hong CheDepartment of Cardiac Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, People's Republic of China.
Jun ZhouDepartment of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Li ZhangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Meng ZhangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Chaozhao LiangDepartment of Urology, The First Affiliated Hospital of Anhui Medical University; Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University; The Institute of Urology, Anhui Medical University, Hefei, People's Republic of China.
Anhui Medical University · CNFirst Affiliated Hospital of Anhui Medical University · CNShenzhen Luohu People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo help with the clinical practice of renal cancer patients, prognostic models are urgently warranted. We hunted and identified prognostic variables associated with recurrence-free survival (RFS) for renal cancer patients. PATIENTS AND

methodsIn this retrospective study, 187 renal cancer patients who had received curative radical/partial nephrectomy between November 2011 and January 2017 were enrolled in the current study. These patients were randomly split into the training (n = 95) and validation sets (n = 92) by the ratio of 1:1. Univariate and multivariable Cox regression analyses were used to establish the nomogram, which was then evaluated by receiver operating characteristic (ROC) and Kaplan-Meier (K-M) analyses.

resultsPatient characteristics and outcomes were well balanced between the training and validation sets; the median RFS values were 54.1 months and 58.9 months for the training and validation cohorts, respectively. The final nomogram included six independent prognostic variables (prothrombin time (%), prothrombin time (second), albumin/globulin ratio, platelets, sex and fibrinogen). The mean values of RFS for the low- and high-risk groups defined by a prognostic formula were 56.22 ± 18.50 months and 49.54 ± 23.57 months, respectively, in the training cohort and were 59.00 ± 19.50 months and 53.32 ± 19.95 months, respectively, in the validation cohort. The significance and stability of the model were tested by the time-dependent K-M model and ROC curves, respectively.

conclusionOur validated prognostic model incorporates variables routinely collected from renal cancer patients, identifying subsets of patients with different survival outcomes, which provides useful information for patient care and clinical trial design.

Indexed as

nomogramrecurrencerenal cancer

Identifiers

PMID32982441
PMCPMC7505717
OpenAlexW3086418553

What OpenQuestion holds

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LicenceCC BY-NC
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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.