Evidence map›Paper›PMID 38954088›Full record

ArticleAnnals of surgical oncology2024

A Nomogram Including Sarcopenia for Predicting Progression-Free Survival in Patients with Localized Papillary Renal Cell Carcinoma: A Retrospective Cohort Study.

Wenhui Su, Yukun Wu, Shufen Liao, Zhiqiang Zhang, Yubing Zhang, Wei Ou, Jiajie Yu, Fangzheng Xiang, Cheng Luo, Fufu Zheng

Abstract read
PubMed Publisher
In one paragraph

Article in Annals of surgical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

10 authors.

Wenhui Su *Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yukun Wu *Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Shufen Liao *Department of Anesthesia Surgery Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Zhiqiang ZhangDepartment of Urology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Yubing ZhangDepartment of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Wei OuDepartment of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Jiajie YuDepartment of Andrology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Fangzheng XiangDepartment of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Cheng LuoDepartment of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China. luoch37@mail.sysu.edu.cn.
Fufu ZhengDepartment of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China. zhengfuf@mail.sysu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBecause of to the removal of subclassification of papillary renal cell carcinoma (pRCC), the survival prognostification of localized pRCC after surgical treatment became inadequate. Sarcopenia was widely evaluated and proved to be a predictive factor for prognosis in RCC patients. Therefore, we comprehensively investigated the survival prediction of the body composition parameters for localized pRCC.

methodsPatients pathologically diagnosed with pRCC between February 2012 and February 2022 in our center were enrolled. The body composition parameters, including skeletal muscle index (SMI), subcutaneous adipose tissue (SAT), and perirenal adipose tissue (PRAT), were measured by the images of preoperative computed tomography (CT). The primary outcome was set as progression-free survival (PFS), and the cutoff values of body composition parameters were calculated by using the Youden from receiver operating characteristic curve (ROC) curves. Univariate and multivariate Cox proportional regression analyses were performed to explore independent risk factors for survival prediction. Then, significant factors were used to construct a prognostic nomogram. The performance of the nomogram was evaluated by Harrell's C-index, calibration curves and time-dependent ROC curves.

resultsA total of 105 patients were enrolled for analysis. With a median follow-up time of 30.48 months, 25 (23.81%) patients experienced cancer progression. The percentage of sarcopenia was 74.29%. Univariate Cox analysis identified that gender, PRAT, SAT, skeletal muscle (SM), sarcopenia, surgical technique, and tumor diameter were associated with progression. Further multivariate analysis showed that sarcopenia (hazard ratio [HR] 0.15, 95% confidence interval [CI] 0.03-0.66), SAT (HR 6.36, 95% CI 2.39-16.93), PRAT (HR 4.66, 95% CI 1.77-12.27), tumor diameter (HR 0.35, 95% CI 0.14-0.86), and surgical technique (HR 2.85, 95% CI 1.06-7.64) were independent risk factors for cancer progression. Then, a prognostic nomogram based on independent risk factors was constructed and the C-index for progression prediction was 0.831 (95% CI 0.761-0.901), representing a reasonable discrimination, the calibration curves, and the time-dependent ROC curves verified the good performance of the nomogram.

conclusionsA prognostic nomogram, including sarcopenia, SAT, PRAT, tumor diameter, and surgical technique, was constructed to calculate the probability of progression for localized pRCC patients and needs further external validation for clinical use in the future.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsNomogramsSarcopeniaAdultAgedBody CompositionFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisProgression-Free SurvivalRetrospective StudiesROC CurveBody compositionNomogramPapillary renal cell carcinomaPrognosisSarcopenia

Identifiers

PMID38954088

What OpenQuestion holds

Textmetadata
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.