Evidence map›Paper›PMID 39449162›Full record

ArticleJournal of cachexia, sarcopenia and muscle2024

Prognostic Value of Systemic Inflammation, Nutritional Status and Sarcopenia in Patients With Amyotrophic Lateral Sclerosis.

Yahui Zhu, Ying Zhang, Mao Li, Jiongming Bai, Hongfen Wang, Xinyuan Pang, Rongrong Du, Jiao Wang, Xusheng Huang

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

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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

9 authors.

Yahui ZhuDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Ying ZhangMedical School of Chinese PLA, Beijing, China.
Mao LiDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Jiongming BaiDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Hongfen WangDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Xinyuan PangDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Rongrong DuDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Jiao WangDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Xusheng HuangDepartment of Neurology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.ORCID 0000-0002-2451-0254

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNutritional status, systemic inflammatory responses and muscle mass are associated with the prognosis of patients with amyotrophic lateral sclerosis (ALS). However, the optimal biomarker for predicting prognosis remains unclear. This study aimed to identify the optimal indicators of survival among the nutrition-based, inflammation-based and muscle mass-related markers for ALS patients.

methodsWe enrolled ALS patients from January 2014 to December 2019. Experienced neurologists followed up with the participants until January 2022. This study included a total of 17 nutritional, systemic inflammatory or muscle mass-related indicators. Maximally selected rank statistics determined the cut-off points for these indicators. Kaplan-Meier estimation was used to assess survival. Uni- and multivariate Cox proportional hazards models were used to determine the effects of indicators on survival. Finally, time-dependent receiver operating characteristic (time-ROC) curves and the C-index were calculated to evaluate the predictive efficacy of different indicators.

resultsA total of 506 patients with ALS were enrolled in this study, including 288 males (56.9%) and 218 females (43.1%), with a mean age of 54.2 ± 10.5 years. Among these ALS patients, 334 cases (68.0%) either died or underwent tracheotomy. In univariate Cox proportional hazards regression, 11 indicators were significantly associated with ALS survival (p < 0.05). And systemic immune inflammation (SII), platelet-to-lymphocyte ratio (PLR), modified geriatric nutritional risk index (mGNRI), creatinine and sarcopenia index (SI, (creatinine/cystatin C) × 100) were determined as independent predictors (p < 0.05) in multivariate Cox proportional hazards regression. A higher SI predicted longer survival (hazard ratio, 0.59; 95% confidence interval [CI], 0.46-0.76; p < 0.001). The results of time-ROC and C-index analyses indicated that SI had the best predictive efficacy for ALS survival, with a C-index of 0.65 (95% CI, 0.54-0.75) for 1-year, 0.61 (95% CI, 0.57-0.65) for 3-year and 0.59 (95% CI, 0.55-0.62) for 5-year survival. Across different subgroups, SI had the highest C-index in men and women, limb onset and aged < 60 year ALS patients, compared with other indicators. However, cystatin C was the best indicator for predicting the survival of ALS patients with bulbar onset, whereas the prognostic nutritional index (PNI) was the best for those aged ≥60 years.

conclusionsThe serum SI demonstrates superior prognostic ability compared to other inflammation-based, nutrition-based and muscle mass-related indicators for patients with ALS. Given its simplicity and availability, it is well suited for clinical use in evaluating the prognosis of ALS patients.

Indexed as

Amyotrophic Lateral SclerosisInflammationNutritional StatusSarcopeniaAdultAgedBiomarkersFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsROC CurveBiomarkersamyotrophic lateral sclerosisinflammationnutritionsarcopenia indexsurvival

Identifiers

PMID39449162
PMCPMC11634485

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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.