Evidence map›Paper›PMID 37015898›Full record

Trial reportCancer medicine2023

Construction of the prognostic model for small-cell lung cancer based on inflammatory markers: A real-world study of 612 cases with eastern cooperative oncology group performance score 0-1.

Chang Liu, Bo Jin, Yunpeng Liu, Ouyang Juhua, Bowen Bao, Bowen Yang, Xiuming Liu, Ping Yu, Ying Luo, Shuo Wang and 7 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
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

17 authors.

Chang LiuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.ORCID 0000-0001-9581-7539
Bo JinDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Yunpeng LiuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Ouyang JuhuaDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Bowen BaoDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Bowen YangDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Xiuming LiuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Ping YuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Ying LuoDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Shuo WangDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Zan TengDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Na SongDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Jinglei QuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Jia ZhaoDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Ying ChenDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Xiujuan QuDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Lingyun ZhangDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.ORCID 0000-0002-5038-065X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis research aimed to explore the relationship between pre-treatment inflammatory markers and other clinical characteristics and the survival of small-cell lung cancer (SCLC) patients who received first-line platinum-based treatment and to construct nomograms for predicting overall survival (OS) and progression-free survival (PFS).

methodsA total of 612 patients diagnosed with SCLC between March 2008 and August 2021 were randomly divided into two cohorts: a training cohort (n = 459) and a validation cohort (n = 153). Inflammatory markers, clinicopathological factors, and follow-up information of patients were collected for each case. Cox regression was used to conduct univariate and multivariate analyses and the independent prognostic factors were adopted to develop the nomograms. Harrell's concordance index (C-index) and time-dependent receiver operating characteristic curve were used to verify model differentiation, calibration curve was used to verify consistency, and decision curve analysis was used to verify the clinical application value.

resultsOur results showed that baseline C-reactive protein/albumin ratio, neutrophil/lymphocyte ratio, NSE level, hyponatremia, the efficacy of first-line chemotherapy, and stage were independent prognostic factors for both OS and PFS in SCLC. In the training cohort, the C-index of PFS and OS was 0.698 and 0.666, respectively. In the validation cohort, the C-index of PFS and OS was 0.727 and 0.747, respectively. The nomograms showed good predictability and high clinical value. Also, our new clinical models were superior to the US Veterans Administration Lung Study Group (VALG) staging for predicting the prognosis of SCLC.

conclusionsThe two prognostic nomograms of SCLC including inflammatory markers, VALG stage, and other clinicopathological factors had good predictive value and could individually assess the survival of patients.

Indexed as

Lung NeoplasmsSmall Cell Lung CarcinomaGroup ProcessesHumansNeoplasm StagingNomogramsPrognosisinflammatory markersnomogramprognostic factorssmall-cell lung cancersurvival

Identifiers

PMID37015898
PMCPMC10166948

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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.