Evidence map›Paper›PMID 33145297›Full record

ArticleAnnals of translational medicine2020

Prognostic nomogram on clinicopathologic features and serum indicators for advanced non-small cell lung cancer patients treated with anti-PD-1 inhibitors.

Rong Chai, Yinxing Fan, Jiayi Zhao, Fan He, Jianong Li, Yiping Han

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Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

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8citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

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

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rong ChaiDepartment of Respiratory and Critical Care Medicine, Changhai Hospital, Navy Military Medical University, Shanghai, China.
Yinxing FanDepartment of Respiratory and Critical Care Medicine, Changhai Hospital, Navy Military Medical University, Shanghai, China.
Jiayi ZhaoDepartment of General Practice Teaching and Research Office, Changhai Hospital, Navy Military Medical University, Shanghai, China.
Fan HeDepartment of Respiratory and Critical Care Medicine, Changhai Hospital, Navy Military Medical University, Shanghai, China.
Jianong LiDepartment of Respiratory and Critical Care Medicine, Changhai Hospital, Navy Military Medical University, Shanghai, China.
Yiping HanDepartment of Respiratory and Critical Care Medicine, Changhai Hospital, Navy Military Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmune checkpoint inhibitors (ICIs) have appeared as a promising therapy regimen for non-small cell lung cancer (NSCLC), but with an unsatisfying therapeutic response and inefficiency of a single predictive biomarker in patients' selection.

methodsCentral data of clinicopathologic features, peripheral blood indicators, and treatment records were collected in advanced NSCLC patients accepting PD-1 inhibitors in Changhai Hospital from July 2016 to September 2019. The OS probability nomogram was developed according to Akaike Information Criterion (stepAIC) selected factors. The predictive accuracy of the nomogram was assessed by discrimination and calibration. C-index and decision curve analysis were used to compare with the previously reported model (Botticelli Model). Computers resampling 500 times (Bootstrap 500 times) were performed to validate the model internally. According to the nomogram-based total point scores (TPS), we divided patients into different risk groups.

resultsA total of 110 patients were enrolled in this study. Six predictors, including liver metastasis, Eastern Cooperative Oncology Group Performance Status (ECOG PS), second- or third-line immunotherapy, baseline levels of CRP, cytokeratin 19 fragment (CYFRA21-1), were selected to set up the nomogram. The C-index of the current nomogram was 0.81 (95% CI: 0.72-0.80), keeping the same accuracy as the earlier one. Calibration plots showed slight underestimation in patients with predictive mortality <44% at 12 months and overestimation in patients with predictive mortality >44%. Decision curve analysis showed that the current nomogram was with a higher net benefit rate than the earlier model. According to the cut-off points of TPS, patients were divided into three subgroups: low risk (TPS ≤118), intermediate-risk (118< TPS ≤189), and high risk (TPS >189). A significant OS difference was observed among subgroups. Median OS was 6.6, 4.5, 1.3 months, respectively.

conclusionsWe proposed a novel nomogram model on easily available and inexpensive clinicopathologic features, peripheral blood indicators which is beneficial in individual risk assessment for advanced NSCLC patients before receiving PD-1 inhibitors, and assisting clinicians in accurately determining therapeutic decisions.

Indexed as

advanced non-small cell lung cancer (advanced NSCLC)clinicopathologic characteristicsimmunotherapyNomogramperipheral blood biomarkers

Identifiers

PMID33145297
PMCPMC7575979

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