Elsevier

The Lancet Oncology

Volume 8, Issue 6, June 2007, Pages 488-499
The Lancet Oncology

Fast track — Articles
Microvessel density as a prognostic factor in non-small-cell lung carcinoma: a meta-analysis of individual patient data

https://doi.org/10.1016/S1470-2045(07)70145-6Get rights and content

Summary

Background

Angiogenesis is a potential prognostic factor that has been investigated in patients with non-small-cell lung carcinoma. However, published studies of the role of angiogenesis as a prognostic factor are inconclusive. We aimed to collect individual patient data to assess microvessel-density counts (ie, a measure of angiogenesis) as a prognostic factor in non-small-cell lung carcinoma.

Methods

We obtained published and unpublished datasets and extracted appropriate data, taking particular care to ensure data quality. Detailed information was obtained for the laboratory methods used by every research centre that generated the data. The outcome of interest was overall survival. We did a meta-analysis to estimate the prognostic role of microvessel density by combining separately estimated hazard ratios (HR) from every study, which were adjusted for tumour stage and age. Analyses were done separately for studies that used the Chalkley method or for those that counted all microvessels.

Findings

17 centres provided data for 3200 patients, 2719 of which were included in the analysis. All but three centres (datasets 9, 10, and 13–367 cases) had already published their findings, and six had updated follow-up information (datasets 1, 2, 3, 6, 7, and 8–1273 cases). For all but three centres (datasets 4, 11, and 13) some data corrections were necessary. For microvessel density counts obtained by the Chalkley method, the HR for death per extra microvessel was 1·05 (95% CI 1·01–1·09, p=0·03) when analysed as a continuous variable. For microvessel density counts obtained by the all vessels method, the HR for death per ten extra microvessels was 1·03 (0.97–1·09, p=0·3) when analysed as a continuous variable.

Interpretation

Microvessel density does not seem to be a prognostic factor in patients with non-metastatic surgically treated non-small-cell lung carcinoma. This conclusion contradicts the results of a meta-analysis of published data only. Therefore, the methodology used to assess prognostic factors should be assessed carefully.

Introduction

Non-small-cell lung carcinoma has a very high mortality.1 Conventional treatment—ie, radical excision without radiotherapy or chemotherapy—is curative for only 40% of patients who are eligible for this treatment.2

Several biological factors, including measures of angiogenesis, have been investigated for their prognostic role. Such research aims to expand understanding of the disease process, identify patients at risk, and, improve clinical outcome. Although there is much anecdotal evidence to suggest that several biological factors have a prognostic role in non-small-cell carcinoma, their statistical investigation and clinical implementation are limited by a lack of consensus on appropriate investigation methods.

Consideration of all relevant evidence on a particular factor in a systematic way is desirable.3 A systematic review identifies relevant studies, extracts relevant data, appraises study methods, and might combine results statistically (ie, meta-analysis). However, application of systematic review principles to prognostic studies poses practical and methodological difficulties.4, 5 First, identification of all published studies for a particular prognostic variable is not easy. Second, most prognostic factors in cancer are continuous variables, but researchers tend to dichotomise them into high and low levels using a cut-off point that is convenient or arbitrary6 and that differs between studies.7 Third, small studies are likely to give unreliable results, and those that show a large prognostic effect are more likely to be published than are those that do not; such publication bias is well recognised.8, 9 Evidence of publication bias in prognostic studies is accumulating: it has been shown in studies of Barrett's oesophagus as a risk factor for cancer;10 has been suspected in other reviews;11 and a review12 of the prognostic role of P53 in head and neck cancer showed that published studies had larger prognostic effects than did unpublished studies. Fourth, issues associated with the methods of these studies are compounded by a generally poor standard of reporting. Riley and colleagues13 reviewed prognostic markers for neuroblastoma and by use of ten different methods of data extraction were able to estimate log HR (with SE) from only 204 (35%) of 575 reports of markers. Furthermore, many researchers might not be able to provide missing data.12

Systematic reviewers might use only summary information extracted from published studies, or they might attempt to retrieve individual patient data. Methodological concerns suggest that a systematic review of prognostic factors, based only on published data might be unreliable.4, 14 Therefore, a multicentre collaborative framework to obtain raw data from as many relevant studies as possible is a desirable approach for investigation of prognostic factors.

Angiogenesis is the process of haphazard new vessel formation required for tumour growth, invasion, and metastasis. Microvessel density is a measure of angiogenesis and a widely studied putative prognostic factor. We aimed to do a study of individual patient data to assess microvessel-density counts as a prognostic factor in non-metastatic surgically treated non-small-cell lung carcinoma, by obtaining data from all identified sources.

Section snippets

The Prognosis In Lung Cancer project

The Prognosis in Lung Cancer (PILC) project—an international collaborative study group—was set-up to obtain individual patient data for study of potential prognostic factors in non-metastatic, surgically treated non-small-cell lung carcinoma. Microvessel-density count was the first factor we assessed between 1999 and 2003 at the Centre for Statistics in Medicine, Oxford, UK, under the guidance of a steering committee. Details of the conduct of this study have been published previously;15, 16 in

Results

Four datasets (4, 6, 8, and 10) were obtained prospectively by collection of data as patients were diagnosed; the remaining datasets were obtained retrospectively from hospital historical records. Two datasets (5 and 7) were generated from some historical records and by collection of prospective data. Sample sizes varied from about 30 patients to nearly 500. 2146 (75%) patients were men (data for sex not available for dataset 10). 1530 (56%) of cases had died; median survival was about 3–4

Discussion

Overall, our analyses give only weak evidence to suggest that microvessel density is a prognostic factor for survival in patients with non-small-cell lung carcinoma when analysed as a continuous variable and measured by use of the Chalkley method. No prognostic effect was observed by measurement of all vessels.

Laboratory developments have helped identify many potential cancer prognostic factors. However, there is no consensus on how to design and analyse prognostic studies, despite several

References (84)

  • L Duchateau et al.

    Individual patient-versus literature-based meta-analysis of survival data: time to event and event rate at a particular time can make a difference, an example based on head and neck cancer

    Control Clin Trials

    (2001)
  • L Stewart et al.

    Meta-analysis of the literature or of individual patient data: is there a difference?

    Lancet

    (1993)
  • SJ Arnott et al.

    Preoperative radiotherapy in esophaheal carcinoma: a meta-analysis using individual patient data

    Int J Radiat Oncol Biol Phys

    (1998)
  • N Malats et al.

    P53 as a prognostic marker for bladder cancer: a meta-analysis and review

    Lancet Oncol

    (2005)
  • JA Sterne et al.

    Publication and related bias in meta-analysis: power of statistical tests and prevalence in the literature

    J Clin Epidemiol

    (2000)
  • PJ Easterbrook et al.

    Publication bias in clinical research

    Lancet

    (1991)
  • PJ Goebell et al.

    The international bladder cancer bank: proposal for a new study concept

    Urol Oncol

    (2004)
  • T Yano et al.

    Vascular endothelial growth factor expression and neovascularisation in non-small cell lung cancer

    Eur J Cancer

    (2000)
  • K Matsuyama et al.

    Tumor angiogenesis as a prognostic marker in operable non-small cell lung cancer

    Ann Thorac Surg

    (1998)
  • Y Ohta et al.

    Tumour angiogenesis and recurrence in stage I non-small cell lung cancer

    Ann Thorac Surg

    (1999)
  • BV Offersen et al.

    Quantification of angiogenesis as a prognostic marker in human carcinomas: a critical evaluation of histopathological methods for estimation of vascular density

    Eur J Cancer

    (2003)
  • F Blanchon et al.

    4-year mortality in patients with non-small-cell lung cancer: development and validation of a prognostic index

    Lancet Oncol

    (2006)
  • SM Dubinett et al.

    Assessing prognosis in non-small-cell lung cancer: Avenues to a more complete picture

    J Clin Oncol

    (2004)
  • K Posther et al.

    The surgical management of lung cancer

    Cancer Invest

    (2006)
  • DG Altman et al.

    Primer: and evidence-based approach to prognostic markers

    Nat Clin Pract Oncol

    (2005)
  • DG Altman

    Systematic reviews of evaluations of prognostic variables

    BMJ

    (2001)
  • DG Altman

    Suboptimal analysis using ‘optimal’ cutpoints

    Br J Cancer

    (1998)
  • DG Altman et al.

    Dangers of using “optimal” cutpoints in the evaluation of prognostic factors

    J Natl Cancer Instit

    (1994)
  • CB Begg et al.

    Publication Bias: a problem in interpreting medical data

    J Royal Stat Soc

    (1988)
  • F Song et al.

    Publication and related bias

    Health Tech Assess

    (2000)
  • S Popat et al.

    Thymidylate synthase expression and prognosis in colorectal cancer: a systematic review and meta-analysis

    J Clin Oncol

    (2003)
  • PA Kyzas et al.

    Selective reporting bias in cancer prognostic factor studies

    J Natl Cancer Instit

    (2005)
  • RD Riley et al.

    A systematic review of molecular and biological tumor markers in neuroblastoma

    Clin Cancer Res

    (2004)
  • DG Altman et al.

    Methodological challenges in the evaluation of prognostic factors in breast cancer

    Breast Cancer Res Treat

    (1998)
  • DG Altman et al.

    Systematic review of multiple studies of prognosis: the feasibility of obtaining individual patient data

  • Trivella M. Systematic reviews of prognostic factor studies. DPhil thesis, University of Oxford;...
  • LA Stewart et al.

    Practical methodology of meta-analysis (overviews) using updated individual patient data

    Stats Med

    (1995)
  • E Passalidou et al.

    Vascular phenotype in angiogenic and non-angiogenic lung non-small cell carcinomas

    Br J Cancer

    (2002)
  • N Weidner et al.

    Tumor angiogenesis and metastasis-correlation in invasive breast carcinoma

    New Engl J Med

    (1991)
  • HW Chalkley

    Method for the quantitative morphologic analysis of tissues

    J Natl Cancer Instit

    (1943)
  • M Decaussin et al.

    Expression of vascular endothelial growth factor (VEGF) and its two receptors (VEGF-R1-Flt1 and VEGF-R2-Flk1/KDR) in non-small cell lung carcinoma (NSCLCs): correlation with angiogenesis and survival

    J Pathol

    (1999)
  • J Mattern et al.

    Vascular endothelial growth factor expression and angiogenesis in non-small cell lung carcinomas. International

    J Oncol

    (1995)
  • Cited by (66)

    • Extraction of unadjusted estimates of prognostic association for meta-analysis: simulation methods as good alternatives to trend and direct method estimation

      2018, Journal of Clinical Epidemiology
      Citation Excerpt :

      The main issues that make systematic reviews of prognostic studies challenging are: a) poor indexing, b) poor reporting of summary measures, c) heterogeneity of studies, and d) selective reporting/publication bias [2,5,6]. Given these, the use of individual patient data (IPD) has been suggested as the best strategy to obtain valid estimates from systematic reviews of prognostic studies [5,7–11]. However, there are major resource implications and only a handful of reviews have attempted to obtain IPD [5,7,8,12,13].

    • Prognostic factors and lung cancers

      2015, Revue des Maladies Respiratoires Actualites
    View all citing articles on Scopus
    View full text