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Review
. 2021 Oct;9(20):1597.
doi: 10.21037/atm-21-4733.

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Yuhang Wang #  1 , Xuefeng Lin #  2 , Daqiang Sun  1   3
Affiliations
Review

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Yuhang Wang et al. Ann Transl Med. 2021 Oct.

Abstract

Objective: To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).

Background: Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and follow-up data, the prognostic model is preferred by researchers.

Methods: PubMed and the Cochrane Library were searched using the items "NSCLC", "prognostic model", "prognosis prediction", and "survival prediction" from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified.

Conclusions: The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.

Keywords: Non-small cell lung cancer (NSCLC); PROBAST; prediction model; prognosis.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/atm-21-4733). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
The literature screening flow chart. Studies published in PubMed in the past one year were searched on April 26, 2021. The key words were: ((prognosis) AND (survival) AND (non-small-cell lung cancer) AND (prediction model) OR (signature) AND (AUC) OR (C-index)). Literatures were excluded by the following exclusion criteria: (I) not a study for the prognosis of NSCLC, (II) a model or signature was not developed, (III) the full articles could not be acquired, (IV) the prediction model was not validated in external datasets, (V) the c-index and sample size of prediction models were not assessed or reported in both training and validation datasets. NSCLC, non-small cell lung cancer.
Figure 2
Figure 2
Nomogram for predicting the survival of patients with lung cancer at 3, 5, and 10 years based on data from TCGA. TCGA, The Cancer Genome Atlas.
See this image and copyright information in PMC

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