Evidence map›Paper›PMID 28281552›Full record

ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2017

Reaching the limits of prognostication in non-small cell lung cancer: an optimized biomarker panel fails to outperform clinical parameters.

Marianna Grinberg, Dijana Djureinovic, Hans Rr Brunnström, Johanna Sm Mattsson, Karolina Edlund, Jan G Hengstler, Linnea La Fleur, Simon Ekman, Hirsh Koyi, Eva Branden and 7 more

Abstract read
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In one paragraph

Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

17 authors.

Marianna GrinbergDepartment of Statistics, TU Dortmund University, Dortmund, Germany.
Dijana DjureinovicDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-1852-5409
Hans Rr BrunnströmDivision of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden.
Johanna Sm MattssonDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Karolina EdlundLeibniz Research Centre for Working Environment and Human Factors (IfADo), TU Dortmund University, Dortmund, Germany.
Jan G HengstlerLeibniz Research Centre for Working Environment and Human Factors (IfADo), TU Dortmund University, Dortmund, Germany.
Linnea La FleurDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Simon EkmanDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Hirsh KoyiDepartment of Respiratory Medicine, Gävle Hospital, Gävle, Sweden.
Eva BrandenDepartment of Respiratory Medicine, Gävle Hospital, Gävle, Sweden.
Elisabeth StåhleDepartment of Clinical Sciences, Uppsala University, Uppsala, Sweden.
Karin JirströmDivision of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden.
Derek K TracyOxleas NHS Foundation Trust, London, UK.
Fredrik PonténDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Johan BotlingDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Jörg RahnenführerDepartment of Statistics, TU Dortmund University, Dortmund, Germany.
Patrick MickeDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous protein biomarkers have been analyzed to improve prognostication in non-small cell lung cancer, but have not yet demonstrated sufficient value to be introduced into clinical practice. Here, we aimed to develop and validate a prognostic model for surgically resected non-small cell lung cancer. A biomarker panel was selected based on (1) prognostic association in published literature, (2) prognostic association in gene expression data sets, (3) availability of reliable antibodies, and (4) representation of diverse biological processes. The five selected proteins (MKI67, EZH2, SLC2A1, CADM1, and NKX2-1 alias TTF1) were analyzed by immunohistochemistry on tissue microarrays including tissue from 326 non-small cell lung cancer patients. One score was obtained for each tumor and each protein. The scores were combined, with or without the inclusion of clinical parameters, and the best prognostic model was defined according to the corresponding concordance index (C-index). The best-performing model was subsequently validated in an independent cohort consisting of tissue from 345 non-small cell lung cancer patients. The model based only on protein expression did not perform better compared to clinicopathological parameters, whereas combining protein expression with clinicopathological data resulted in a slightly better prognostic performance (C-index: all non-small cell lung cancer 0.63 vs 0.64; adenocarcinoma: 0.66 vs 0.70, squamous cell carcinoma: 0.57 vs 0.56). However, this modest effect did not translate into a significantly improved accuracy of survival prediction. The combination of a prognostic biomarker panel with clinicopathological parameters did not improve survival prediction in non-small cell lung cancer, questioning the potential of immunohistochemistry-based assessment of protein biomarkers for prognostication in clinical practice.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungCell Adhesion Molecule-1Enhancer of Zeste Homolog 2 ProteinGlucose Transporter Type 1HumansImmunohistochemistryIntracellular Signaling Peptides and ProteinsLung NeoplasmsNuclear ProteinsPrognosisThyroid Nuclear Factor 1Tissue Array AnalysisBiomarkers, TumorCell Adhesion Molecule-1Enhancer of Zeste Homolog 2 ProteinEZH2 protein, humanGlucose Transporter Type 1Intracellular Signaling Peptides and ProteinsNIFK protein, humanNKX2-1 protein, humanNuclear ProteinsSLC2A1 protein, humanThyroid Nuclear Factor 1

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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.