Evidence map›Paper›PMID 31167668›Full record

ArticleBMC palliative care2019

Nomogram-based parameters to predict overall survival in a real-world advanced cancer population undergoing palliative care.

Weiwei Zhao, Zhiyong He, Yintao Li, Huixun Jia, Menglei Chen, Xiaoli Gu, Minghui Liu, Zhe Zhang, Zhenyu Wu, Wenwu Cheng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC palliative care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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  5. Development and external validation of a predictive multivariable model for last-weeks survival of advanced cancer patients in the palliative home care setting (PACS).Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Article
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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

10 authors.

Weiwei ZhaoDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhiyong HeDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Yintao LiDepartment of Oncology, Shandong Cancer Hospital, Shandong Academy of Medical Sciences, Jinan, China.
Huixun JiaDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Menglei ChenDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Xiaoli GuDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Minghui LiuDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhe ZhangDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhenyu WuDepartment of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China. zyw@fudan.edu.cn.
Wenwu ChengDepartment of Integrated Therapy, Fudan University Shanghai Cancer Center, Shanghai, China. cwwxxm@sina.com.

Funding

National Natural Science Foundation of China 81400810
6 · The paper itself

Abstract

backgroundAlthough palliative care has been accepted throughout the cancer trajectory, accurate survival prediction for advanced cancer patients is still a challenge. The aim of this study is to identify pre-palliative care predictors and develop a prognostic nomogram for overall survival (OS) in mixed advanced cancer patients.

methodsA total of 378 consecutive advanced cancer patients were retrospectively recruited from July 2013 to October 2015 in one palliative care unit in China. Twenty-three clinical and laboratory characters were collected for analysis. Prognostic factors were identified to construct a nomogram in a training cohort (n = 247) and validated in a testing cohort (n = 131) from the setting.

resultsThe median survival time was 48.0 (95% CI: 38.1-57.9) days for the training cohort and 52.0 (95% CI: 34.6-69.3) days for the validation cohort. Among pre-palliative care factors, sex, age, tumor stage, Karnofsky performance status, neutrophil count, hemoglobin, lactate dehydrogenase, albumin, uric acid, and cystatin-C were identified as independent prognostic factors for OS. Based on the 10 factors, an easily obtained nomogram predicting 90-day probability of mortality was developed. The predictive nomogram had good discrimination and calibration, with a high C-index of 0.76 (95% CI: 0.73-0.80) in the development set. The strong discriminative ability was externally conformed in the validation cohort with a C-index of 0.75.

conclusionsA validated prognostic nomogram has been developed to quantify the risk of mortality for advanced cancer patients undergoing palliative care. This tool may be useful in optimizing therapeutic approaches and preparing for clinical courses individually.

Indexed as

NomogramsAgedChinaChi-Square DistributionFemaleHumansMaleMiddle AgedNeoplasmsPalliative CareProportional Hazards ModelsRetrospective StudiesSurvival RateTime FactorsAdvanced cancerNomogramPalliative careSurvival prediction

Identifiers

PMID31167668
PMCPMC6551870

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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.