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Study protocol: systematic review and meta-analysis of randomized controlled trials in first-line treatment of squamous non-small cell lung cancer

Abstract

Background

There is a high unmet need for effective treatments for patients with squamous non-small cell lung cancer (NSCLC). Eli Lilly and Company is conducting a phase III, randomized, multicenter, open-label study of gemcitabine plus cisplatin plus necitumumab (GC + N) versus gemcitabine plus cisplatin (GC) for the first-line treatment of patients with stage IV squamous NSCLC. Given GC is not the only treatment commonly used for the treatment of squamous NSCLC, this study was designed to compare the survival, toxicity, and quality of life outcomes of current treatment strategies for squamous NSCLC in the first-line setting.

Methods/Design

A systematic review and meta-analysis (including indirect comparisons) of treatments used in squamous NSCLC will be conducted to assess the clinical efficacy (overall and progression-free survival), health-related quality of life (HRQoL), and safety (grade 3–4 toxicity) of GC + N compared to other treatments used in squamous NSCLC. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines will be followed for all aspects of this study. A systematic literature review will be conducted to identify randomized controlled trials evaluating chemotherapy treatment in first-line NSCLC. Eligible articles will be restricted to randomized controlled trials (RCTs) among chemotherapy-naïve advanced NSCLC cancer patients that report outcome data (survival, toxicity, or quality of life) for patients with squamous histology. Following data extraction and validation, data consistency and study heterogeneity will be assessed. A network meta-analysis will be conducted based on the available hazard ratios for overall and progression-free survival, odds ratios for published toxicity data, and mean difference of HRQoL scales. Sensitivity analyses will be conducted.

Discussion

This is a presentation of the study protocol only. Results and conclusions are pending completion of this study.

Systematic review registration

PROSPEROCRD42014008968

Peer Review reports

Background

Lung cancer is the leading cause of cancer-related deaths worldwide, accounting for 1.3 million deaths annually[1]. It is defined as cancer that forms in the tissues of the lung, usually in the cells lining air passages, and is divided into two main subtypes: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). NSCLC is the predominant subtype form and accounts for about 85% of all lung cancers[2]; it is further divided by cell histology into adenocarcinoma, squamous cell carcinoma, and large-cell carcinoma, with adenocarcinoma the currently predominant histology. Although the overall age-adjusted incidence rates for lung cancer are declining in many developed nations, lung cancer remains the leading cause of cancer-related deaths worldwide with an overall 5-year survival rate of about 15%[3], resulting in a significant disease burden worldwide.

The treatment of lung cancer is based on the type and stage of tumor, as well as the patient’s general medical condition. For patients diagnosed with early stage disease (i.e., stages I and II), surgery offers the best option for survival and cure. Adjuvant chemotherapy is increasingly used in those with stage II disease and occasionally for those with stage IB, depending on the size of the tumor. For those with stage III lung cancer, chemoradiotherapy alone or in addition to surgery is used to treat patients; however, while treatment is administered with a curative intent, the 5-year survival for patients with regional disease is approximately 26%, which decreases to 3.9% for patients with metastatic disease[3]. Treatment for patients with advanced disease tends to be palliative, although extension in survival may be achieved. The standard first-line drug treatments for advanced NSCLC, neoadjuvant, adjuvant, or chemoradiotherapy, are generally based on the combination of a second- or third-generation cytotoxic drug with a platinum agent (cisplatin or carboplatin).

There are many drug therapies available for treatment of NSCLC; however, not all current therapies are suitable for use in tumors of all histologies. The results of clinical trials have indicated that drugs such as pemetrexed have greater efficacy among patients with adenocarcinoma than those with other NSCLC histologies (e.g., squamous cell carcinoma)[4]. Other newer agents, such as bevacizumab, are indicated for adenocarcinoma because of higher toxicities observed in patients with squamous histology[5]. Drugs such as erlotinib and gefitinib are not restricted by histology, but have greater efficacy among patients with epidermal growth factor receptor (EGFR) mutations[6, 7]. The frequency of EGFR mutations in patients with squamous cell carcinoma, as opposed to those with adenocarcinoma, is very low[8]. Therefore, histology-specific treatment options are limited for patients with squamous cell carcinoma, which accounts for about 25% of all non-small cell lung cancers[9].

There is thus a high unmet need for effective treatments for patients with squamous NSCLC, as disease burden is large and there is currently a lack of targeted drug therapies for NSCLC squamous cell tumors. Eli Lilly and Company is currently developing necitumumab as a first-line treatment in patients with stage IV squamous NSCLC. The current phase III study (ClinicalTrials.gov identifier: NCT00981058) is a randomized, multicenter, open-label study of gemcitabine-cisplatin chemotherapy plus necitumumab (GC + N) versus gemcitabine-cisplatin (GC) chemotherapy alone in first-line treatment of patients with stage IV squamous NSCLC. The target patient population for this trial is comprised of male and female patients with histologically or cytologically confirmed, advanced squamous NSCLC, previously untreated for metastatic disease.

The purpose of this systematic literature review and meta-analysis is to compare survival, toxicity, and quality of life outcomes of current treatment strategies with necitumumab among patients with squamous NSCLC.

Methods/Design

This systematic literature review and meta-analysis (including indirect comparisons) will be conducted of treatments used in squamous NSCLC to assess the clinical efficacy, quality of life, and safety of GC + N compared to other treatments used in squamous NSCLC. To complete this objective, the following specific aims will be pursued:

  1. 1.

    To conduct a systematic literature review of randomized trials of all relevant treatments used for the first-line treatment of advanced squamous NSCLC;

  2. 2.

    To extract relevant data from the relevant published literature;

  3. 3.

    To perform indirect and direct comparisons of GC + N to all identified comparators for the following outcomes:

    1. 3.1

      Overall survival;

    2. 3.2

      Progression-free survival;

    3. 3.3

      Toxicity; and

    4. 3.4

      Quality of life

Search strategy

Searches will be conducted in PubMed, Ovid/MEDLINE, and Embase using free text and controlled vocabulary terms (MeSH). Studies published prior to 1995 will be excluded as NSCLC histology was not clearly differentiated at that time. Studies not published in English will be excluded. Comparisons will be made across all regimens and not just limited to "add-on" therapies. Tables 1,2, and3 detail the specific search strategies for PubMed, Ovid, and Embase, respectively.

Table 1 PubMed search strategy
Table 2 Embase search strategy
Table 3 Ovid/MEDLINE search strategy

The following is a list of the conference databases that will be searched:

  •  American Association for Cancer Research, AACR

  •  American College of Radiation Oncology

  •  American Society for Radiation Oncology, ASTRO

  •  American Society of Clinical Oncology, ASCO

  •  Asia Pacific Lung Cancer Conference, APLCC

  •  Asia Pacific Oncology Summit, APOS

  •  Asian Oncology Summit, AOS

  •  Atualizacoes em Oncologia

  •  Australian Lung Cancer Conference, ALCC

  •  Austrian Society of Haematology and Oncology, ASHO

  •  The Association for Cancer Surgery, BASO

  •  Biennial Congress of the European Association for Cancer Research, EACR

  •  British Thoracic Oncology Group Conference, BTOG

  •  Clinical Oncology Society of Australia, COSA

  •  Cancer Symposium of the Society of Surgical Oncology, CSSSO

  •  Chicago Supportive Oncology Conference, CSOC

  •  Clinical Interventional Oncology, CIO

  •  Congres National de la Societe Francaise de Radiotherapie Oncologique, SFRO

  •  Congress of the European Society for Medical Oncology, ESMO

  •  Congress of the European Society of Surgical Oncology, ESSO

  •  Congress of the International Society of Oncology and Biomarkers, ISOBM

  •  Educational Cancer Convention Lugano of the European School of Oncology, ECCLU

  •  European Lung Cancer Conference, ELCC

  •  European Multidisciplinary Cancer Congress

  •  European Multidisciplinary Conference in Thoracic Oncology, EMCTO

  •  Hematology Oncology Pharmacy Association Annual Meeting, HOPA

  •  International Conference and Exhibition on Cancer Science and Therapy, IMPAKT

  •  International Conference of the Society for Integrative Oncology

  •  International Lung Cancer Congress

  •  International Symposium on Targeted Anticancer Therapies, TAT

  •  Italian Society of Surgical Oncology Conference

  •  Medical Oncology Group of Australia, MOGA

  •  Oncology Platform and Poster Presentation, CSM 2009

  •  Scientific Association of Swiss Radiation Oncology, SASRO

  •  Scientific Meeting of the International Society for Biological Therapy of Cancer

  •  Scientific Meeting of the Society for Immunotherapy of Cancer, SITC

  •  Symposium of the International Society of Oncology Pharmacy Practitioners

  •  UK Radiation Oncology Conference

  •  World Conference on Interventional Oncology, WCIO

  •  World Congress on Cancer Science and Therapy

Eligibility assessment

To be eligible, published studies must meet the criteria outlined in Table 4. Briefly, eligible articles must report at least one of the following outcomes (overall survival, progression-free survival, quality of life, or toxicity) for patients with squamous NSCLC. Eligible articles must report data from randomized controlled trials published since 1995. Abstracts of all potentially eligible citations will be reviewed and excluded if it can be definitively stated that no eligibility criterion is met. All other publications will be considered potentially eligible. Full-text articles of all potentially eligible citations will be obtained and reviewed to determine final eligibility. The eligibility of both the abstracts and full-text articles will be assessed independently by two reviewers using the criteria and screening matrix presented in Table 4. If the two reviewers do not agree on the eligibility of an article, a third reviewer will serve as the tie breaker. Systematic reviews and other review articles will be scanned to ensure no eligible randomized controlled trials (RCTs) are missed.

Table 4 Eligibility criteria and screening matrix

Data extraction and verification

In a process similar to that used for assessing eligibility, two reviewers will independently extract the data elements listed in Table 5 from each eligible article. These data are extensive and it is not expected, nor is it required, that all studies will report all data fields included. However, attempts to collect as extensive of data as possible will be made to increase the potential range of sensitivity and descriptive analyses. In addition to the data extraction, two reviewers will also assess bias using the Cochrane Risk of Bias Tool and will measure study quality using the Physiotherapy Evidence Database (PEDro) scale (see the "Assessment of bias and study quality" section). Data from both reviewers will be compared. If any data element does not match, the reviewers will meet and attempt to resolve the discrepancies. In cases of non-resolution, a third reviewer will be consulted. All rules and decision criteria used in the data resolution process will be recorded for quality assurance and methodological consistency purposes. To further ensure the accuracy of the extracted data, a subset of 10% of all extracted articles will be verified by an individual not involved in the data extraction process. In cases of error detection, the full database will be reviewed to ensure accuracy.

Table 5 Variables for data extraction

Analysis plan

A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) diagram will be developed based on the search strategy and eligibility assessment to show the flow of included and excluded studies. The descriptive statistics from each trial of patients with squamous cell carcinoma will be included and described. These variables will include treatment group, number of patients, mean age (standard deviation), number and percent male, number and percent with stage IV disease, overall survival, progression-free survival, toxicity, and quality of life.

A network diagram visually describing existing treatments for squamous NSCLC will be created after all eligible studies have been identified. However, some publications may not present data in a format that allows them to be included in the study despite otherwise meeting eligibility criteria (e.g., mixed populations not reported separately, mixed histologies not reported separately, mixed lines of therapy not reported separately). In the case of a disconnected network resulting from the absence of data for the appropriate patient population, authors of such articles will be contacted and asked to provide the needed data from their publications that would enable connection to the studied network.

The primary purpose of this study is to perform indirect and direct comparisons of GC + N versus all identified comparators for overall survival (OS) and progression-free survival (PFS). Individual hazard ratios (HR) or median time-to-event (median time) and 95% confidence intervals (90% or 99% confidence intervals will be converted to 95%) for overall survival will be included in the network meta-analysis using a Bayesian approach that ensures the preservation of randomization in the network[10]. The HR will be used as the primary unit of analyses to evaluate differences in effect size between treatment groups. Data for analysis will be extracted directly from the text of each eligible article, calculated from data included in the text, or extrapolated from the Kaplan-Meier plot according to the method of Parmar and colleagues[11]. Graphs and figures will be digitized using TechDig software and/or xyscan tool (Debian, Inc) if necessary, and digitized values will be extracted.

Heterogeneity will be explored by comparing the fixed and random effects models to ensure that the network has good properties. Additionally, heterogeneity will be explored by visual inspection of forest plots. The consistency assumption will be tested by examining network diagrams to identify any closed "loops" where inconsistencies can occur. When the network is complex with multiarm trials, the "node-splitting" approach defined by Dias and colleagues[12] will be used to identify inconsistencies. Density plots of the posterior samples from models based on direct, indirect, and mixed evidence will be compared. In addition, the heterogeneity parameters (variance and standard deviation) and goodness of model fit measures (residual deviance and deviance information criterion (DIC), a Bayesian criterion for model comparison) between the direct and indirect models will be compared.

OS and PFS data will be analyzed using a log transformation of the HR and treating this as a continuous outcome. For studies with median time information, we will also use log transformation of the median time and treat this as a continuous outcome in sensitivity analyses. HRs are preferred summary statistics to median time per Michiels and colleagues[13], and hence, the analysis will utilize HR data for the primary outcome measure.

Ideally, the literature will provide values for log (HR) and the standard error (SE) for log (HR). If the SE for log (HR) is not available, an attempt will be made to estimate the missing value from the SE for median time, assuming an exponential distribution of survival time and log (HR) = -log (median time ratio). Alternatively, an estimate of the SE for log (HR) will be made on the basis of the number of subjects with events as specified below:

  1. 1.

    "MedianTime" will be converted into log (median time);

  2. 2.

    The SE for log (median time) is estimated as (log(upper confidence limit) - log (lower confidence limit))/2/quantile (confidence level) if a treatment arm has non-missing value for all three variables;

  3. 3.

    If confidence limit is missing, then the number of subjects with events can be used to estimate the standard error for log (median time) as 1/sqrt(n) for a treatment arm.

Individual odds ratios and/or toxicity rates for each grade 3–4 toxicity from each study will be included, respectively, in an NMA using a Bayesian approach that ensures the preservation of randomization in the network. Odds ratios will be calculated for studies reporting toxicity rates. Prior to creating the odds ratios, we will ensure that similar versions of toxicity scaling criteria have been used. Data for analysis will be directly extracted from the text of the article or calculated from data in the text.

A network meta-analysis of GC + N to all identified comparators will be conducted for health-related quality of life (HRQoL) measures (including EQ-5D and the Lung Cancer Symptom Scale (LCSS)) during and following therapy. The most common quality of life instruments as reported across studies will be analyzed. Initial analyses will be limited to those quality of life outcomes for which GC + N data are available. For each identified measure, a standardized mean difference in quality of life outcomes from each study will be included. First, the number of trials per HRQoL instrument will be determined. If the number of trials per HRQoL instrument is 2 or more, then these data will be analyzed. For each instrument, data will be assessed according to the guidelines for that particular instrument and then pooled across studies to determine the standardized mean difference.

A meta-regression will be conducted using the key covariates of patient age and stage of disease (percent of patients with stage IV), as these variables have prognostic value in squamous NSCLC. Additional covariates may be identified following the literature review and will be considered for inclusion in post hoc analyses to control for potential bias.

Sensitivity analyses

We anticipate that some studies will not report all relevant data. In order that such studies can still be included in the analysis, we may consider imputing missing data using established methods as appropriate[14]. If imputation is made, the Bayesian model as described above will be used as the primary analysis and will be compared with analyses including the imputed values. Sensitivity analyses may be conducted to examine the effect of this method using an approach proposed by Carpenter and colleagues[15], which entails imputing missing data under a missing at random assumption, and then reweighting the imputed data to allow for non-random selection. Sensitivity analyses as outlined for OS and PFS will also be conducted for HRQoL; however, the use of disparate HRQoL instruments or assessment time points may result in an inability to evaluate the study endpoint. Sensitivity analyses will be performed to assess the robustness of the findings. At a minimum, the following analyses will be conducted if there are at least three studies available for analysis:

  1. 1.

    Repeat the meta-analysis using a frequentist approach;

  2. 2.

    HR only (primary aim) versus HR or median time;

  3. 3.

    By geographical site of study enrollment;

    1. a.

      e.g., Western versus Eastern hemispheres

    2. b.

      e.g., Americas versus Europe versus Asia

  4. 4.

    Limit to patients with stage IV disease;

  5. 5.

    Direct comparisons only;

  6. 6.

    By excluding phase II trials;

  7. 7.

    By age—studies with a mean age over the age of 70;

  8. 8.

    Limiting the analysis to high-quality studies (≥6) as determined by the PEDro scale;

  9. 9.

    Removing studies considered to be biased according to the Cochrane Risk of Bias Tool.

Assessment of bias and study quality

The risk of bias will be appraised using the Cochrane Risk of Bias Tool (http://www.cochrane-handbook.org). This tool was developed specifically to assess the internal validity of RCTs. It consists of the following seven criteria: 1) randomization generation, 2) allocation concealment, 3) blinding of outcome assessors, 4) blinding patients and personnel, 5) incomplete outcome data (i.e., withdrawals), 6) selective outcome reporting, and 7) other risks of bias. The final item will include fraudulent results, other methodological flaws in the RCTs, and the potential for bias.

To assess publication bias, the fail-safe N will be calculated. If the number of unpublished trials that may invalidate the findings is less than five, it will be noted in the conclusions as a potential limitation of the findings. If the number of unpublished trials to invalidate the findings is five or greater, it will be noted in the results. Furthermore, funnel plot analyses will also be conducted to provide a visual representation demonstrating where unpublished data may exist. This is planned to help guide the interpretation of the study findings and the direction of bias.

Quality of selected trials for inclusion in the review will be assessed. The PEDro quality scale, an 11-item scale designed for rating the methodological quality of randomized controlled trials[16], will be used to evaluate the quality of selected trials. Here the two reviewers will independently assess studies for methodological validity prior to inclusion. Identified studies that meet the inclusion criteria will then be grouped according to the class of statin used in the trial. High quality scores will be defined as a PEDro score ≥6 and low quality scores will be defined as a PEDro score <6.

Missing data are expected in the majority of data fields collected in this meta-analysis. In cases of missing data, heterogeneity will be tested on all outcome variables to ensure that studies are comparable. Forest plots will be created for OS, PFS, toxicity, and quality of life endpoints. In the case of non-overlapping confidence intervals, the research team will discuss the need for post hoc subgroup analyses.

Discussion

The study design for this systematic review and meta-analysis is presented here to follow PRISMA standards. Industry-sponsored or industry-led studies are increasingly under scrutiny regarding transparency and risk of bias[17]. This study protocol has been designed prior to any knowledge of the study data or outcomes from existing published literature and is being disseminated in an attempt to provide the scientific community with the ability to evaluate the methods and plans of our study before it is conducted. The study protocol has been designed to meet PRISMA standards[18, 19] and is being disclosed so that our methods can be retrieved and evaluated against the final analyses and interpretation of findings.

While it is almost impossible to fully anticipate the limitations of the data once they are obtained, this study has been designed in an attempt to pre-specify all primary analyses and sensitivity analyses to demonstrate the stability in results that may be discovered. However, it is possible that there will not be sufficient data to achieve all the pre-specified study aims or to complete all planned analyses. There are also possible limitations in the network connections. Unlike patients diagnosed with lung cancers of non-squamous histology, those with squamous NSCLC have not benefited from the same depth and breadth of research conducted to identify optimal treatment strategies. Therefore, via our search criteria, we are casting a wide net in the hopes of finding studies that not only investigate, but also report, outcomes for this histological subgroup.

Our ultimate goal is to provide reliable and trustworthy data regarding the comparative efficacy of necitumumab against other possible options for care so that decision makers can come to their own conclusions regarding the value of this molecule currently in development.

References

  1. ALA: Lung Cancer Fact Sheet - American Lung Association. 2013, [http://www.lung.org/lung-disease/lung-cancer/resources/facts-figures/lung-cancer-fact-sheet.html],

    Google Scholar 

  2. CancerCare: Lung Cancer 101. 2013, [http://www.lungcancer.org/find_information/publications/163-lung_cancer_101/268-types_and_staging],

    Google Scholar 

  3. SEER: "Cancer Statistics." Cancer of the Lung and Bronchus. 2013, [http://seer.cancer.gov/statfacts/html/lungb.html],

    Google Scholar 

  4. Scagliotti G, Hanna N, Fossella F, Sugarman K, Blatter J, Peterson P, Simms L, Shepherd FA: The differential efficacy of pemetrexed according to NSCLC histology: a review of two phase III studies. Oncologist. 2009, 14 (3): 253-263. 10.1634/theoncologist.2008-0232.

    Article  CAS  PubMed  Google Scholar 

  5. Johnson DH, Fehrenbacher L, Novotny WF, Herbst RS, Nemunaitis JJ, Jablons DM, Langer CJ, DeVore RF, Gaudreault J, Damico LA, Holmgren E, Kabbinavar F: Randomized phase II trial comparing bevacizumab plus carboplatin and paclitaxel with carboplatin and paclitaxel alone in previously untreated locally advanced or metastatic non-small-cell lung cancer. J Clin Oncol. 2004, 22 (11): 2184-2191. 10.1200/JCO.2004.11.022.

    Article  CAS  PubMed  Google Scholar 

  6. AstraZeneca: Iressa. Gefinitib. 2014, [http://www.iressa.com],

    Google Scholar 

  7. Genentech: Erlotinib Tablets. 2013, [http://www.tarceva.com],

    Google Scholar 

  8. Gahr S, Stoehr R, Geissinger E, Ficker JH, Brueckl WM, Gschwendtner A, Gattenloehner S, Fuchs FS, Rieker RJ, Hartmann A, Ruemmele P, Dietmaier W: EGFR mutational status in a large series of Caucasian European NSCLC patients: data from daily practice. Br J Cancer. 2013, 109 (7): 1821-1828. 10.1038/bjc.2013.511.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Howlader N, Noone AM, Krapcho M, Garshell J, Neyman N, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Cho H, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA: SEER Cancer Statistics Review, 1975–2010. 2013, Bethesda: N.C. Institute

    Google Scholar 

  10. Shen W, Zhu B, Han B, Natanegara F: Bayesian Network Meta-Analysis for Health Technology Assessment and Evaluation for Investigative Treatment. ICSA/ISBS Joint Statistical Conference: 9–12 June 2013. 2013, Washington, DC

    Google Scholar 

  11. Parmar MK, Torri V, Stewart L: Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med. 1998, 17 (24): 2815-2834. 10.1002/(SICI)1097-0258(19981230)17:24<2815::AID-SIM110>3.0.CO;2-8.

    Article  CAS  PubMed  Google Scholar 

  12. Dias S, Welton NJ, Caldwell DM, Ades AE: Checking consistency in mixed treatment comparison meta-analysis. Stat Med. 2010, 29 (7–8): 932-944.

    Article  CAS  PubMed  Google Scholar 

  13. Michiels S, Piedbois P, Burdett S, Syz N, Stewart L, Pignon JP: Meta-analysis when only the median survival times are known: a comparison with individual patient data results. Int J Technol Assess Health Care. 2005, 21 (1): 119-125.

    Article  PubMed  Google Scholar 

  14. Littell JH, Pillai V: Systematic Reviews and Meta-Analysis. 2008, New York: Oxford University Press

    Book  Google Scholar 

  15. Carpenter J, Rucker G, Schwarzer G: Assessing the sensitivity of meta-analysis to selection bias: a multiple imputation approach. Biometrics. 2011, 67 (3): 1066-1072. 10.1111/j.1541-0420.2010.01498.x.

    Article  PubMed  Google Scholar 

  16. de Morton NA: The PEDro scale is a valid measure of the methodological quality of clinical trials: a demographic study. Aust J Physiother. 2009, 55 (2): 129-133. 10.1016/S0004-9514(09)70043-1.

    Article  PubMed  Google Scholar 

  17. Lundh A, Sismondo S, Lexchin J, Busuioc OA, Bero L: Industry sponsorship and research outcome. Cochrane Database Syst Rev. 2012, 12: MR000033

    Google Scholar 

  18. Liberati A, Altman DG, Teztlaff J, Mulrow C, Gøtszche PC, Ioannidis JPA, Clarke M, Devereaux PJ, Kleijnen J, Moher D: The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009, 339: b2700-10.1136/bmj.b2700.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Moher D, Liberati A, Teztlaff J, Altman DG: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009, 339: b2535-10.1136/bmj.b2535.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This study was funded by Eli Lilly and Company.

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Authors and Affiliations

Authors

Corresponding author

Correspondence to Lisa M Hess.

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Competing interests

All study authors disclose that they are employees of Eli Lilly and Company.

Authors’ contributions

AD participated in the study design, development of the study protocol, drafting of the analysis plan, and writing of the manuscript and will be responsible for data and eligibility review. JB conceived of the study design, review of the study protocol, and substantive input to the manuscript. FN developed the study protocol analysis plan and will be responsible for final analyses. LZ developed the study protocol analysis plan and will be responsible for final analyses. ZC developed the study protocol analysis plan and will be responsible for final analyses. SA will be responsible for data and eligibility review. LB and JT conceived of the study design and development of the study protocol. LH conceived of the study design, development of the study protocol, writing of the manuscript, and drafting of the analysis plan and will be responsible for data and eligibility review. All authors reviewed and approved the final version of the manuscript.

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DeLozier, A.M., Brown, J., Natanegara, F. et al. Study protocol: systematic review and meta-analysis of randomized controlled trials in first-line treatment of squamous non-small cell lung cancer. Syst Rev 3, 102 (2014). https://doi.org/10.1186/2046-4053-3-102

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