Are Lung Cancer Publications Up-to-Date in terms of Advances in Statistics and Bioinformatics?


Abstract views: 45 / PDF downloads: 29

Authors

  • Seval Kul epartment of Biostatistics, Gaziantep University School of Medicine
  • İlkay Doğan 2Department of Biostatistics, Faculty of Veterinary, Afyon Kocatepe University

DOI:

https://doi.org/10.5152/EurJTher.2018.1012

Keywords:

Regression analysis, statistical methods, e-learning

Abstract

This study was performed to evaluate whether literature of lung cancer follow advances in statistics and bioinformatics. Four medical journals with high impact factors were reviewed between January 2013 and December 2017. Among 1649 published manuscript, 514 of them were about lung cancer. Also, Medline was searched with key words combinations of e-learning AND education AND cancer AND patient for last 5 years. New statistical methods weren’t applied in the cancer researches performed by clinicians. Furthermore, unlike increasing number of successful studies using internet and computer technologies, number of the study is limited. Working with professional statisticians or collaboration to Biostatisticians will increase the quality of lung cancer papers.

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References

Swinscow TD. Statistics at Square One. IV. Variation between samples. Br Med J 1976; 1: 1585.

Vandenbroucke JP, von Elm E, Altman DG, Gotzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med 2007; 4: e297.

Campbell MK, Piaggio G, Elbourne DR, Altman DG, Consort Group. Consort 2010 statement: extension to cluster randomized trials. BMJ 2012; 345: e5661.

Strasak AM, Zaman Q, Pfeiffer KP, Göbel G, Ulmer H. Statistical errors in medical research--a review of common pitfalls. Swiss Med Wkly 2007; 137: 44-9.

Parsons NR, Price CL, Hiskens R, Achten J, Costa ML. An evaluation of the quality of statistical design and analysis of published medical research: results from a systematic survey of general orthopedic journals. BMC Med Res Methodol 2012; 12: 60.

Thiese MS, Arnold ZC, Walker SD. The misuse and abuse of statistics in biomedical research. Biochem Med (Zagreb) 2015; 25: 5-11.

Mahapatra D, Agarwal K, Khosrowabadi R, Prasad DK. Recent Advances in Statistical Data and Signal Analysis: Application to Real World Diagnostics from Medical and Biological Signals. Comput Math Methods Med 2016; 2016: 1643687.

Suresh K, Chandrashekara S. Sample size estimation and power analysis for clinical research studies. J Hum Reprod Sci 2012; 5: 7-13.

Bland JM, Altman DG. Survival probabilities (the Kaplan-Meier method). BMJ 1998; 317: 1572-80.

Austin PC, Lee DS, Fine JP. Introduction to the analysis of survival data in the presence of competing risks. Circulation 2016; 133: 601-9.

Bakoyannis G, Touloumi G. Practical methods for competing risks data: a review. Stat Medhods Med Res 2012; 21: 257-72.

Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C. Assessing bias in studies of prognostic factors. Ann Intern Med 2013; 158: 280-6.

Skelly AC, Dettori JR, Brodt ED. Assessing bias: the importance of considering confounding. Evid Based Spine Care J 2012; 3: 9-12.

Ruiz JG, Mintzer MJ, Leipzig RM. The impact of E-learning in medical education. Acad Med 2006; 81: 207-12.

Cook DA, Levinson AJ, Garside S, Dupras DM, Erwin PJ, Montori VM. Internet-based learning in the health professions: a meta-analysis. JAMA 2008; 300: 1181-96.

Hurling R, Catt M, Boni MD, Fairley BW, Hurst T, Murray P, et al. Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial. J Med Internet Res 2007; 9: e2.

Hamine S, Gerth-Guyette E, Faulx D, Green BB, Ginsburg AS. Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. J Med Internet Res 2015; 17: e52.

Wu C, Shi X, Cui Y, Ma S. A penalized robust semiparametric approach for gene–environment interactions. Statistics in medicine. 2015; 34: 4016-30.

Wu C, Jiang Y, Ren J, Cui Y, Ma S. Dissecting gene‐environment interactions: A penalized robust approach accounting for hierarchical structures. Stat Med 2018; 37: 437-56.

Schipper MJ, Taylor JM, TenHaken R, Matuzak MM, Kong FM, Lawrence TS. Personalized dose selection in radiation therapy using statistical models for toxicity and efficacy with dose and biomarkers as covariates. Stat Med 2014; 33: 5330-9.

Hajian-Tilaki K. Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J Intern Med 2013; 4: 627-35.

Wang D, Attwood K, Tian L. Receiver operating characteristic analysis under tree orderings of disease classes. Stat Med 2016; 35: 1907-26.

Branscum AJ, Johnson WO, Hanson TE, Baron AT. Flexible regression models for ROC and risk analysis, with or without a gold standard. Stat Med 2015; 34: 3997-4015.

Gasparrini A. Modeling exposure–lag–response associations with distributed lag non‐linear models. Stat Med 2014; 33: 881-99.

Milne RA, Puts MT, Papadakos J, Le LW, Milne VC, Hope AJ, et al. Predictors of High eHealth Literacy in Primary Lung Cancer Survivors. J Cancer Educ 2015; 30: 685-92.

Corbeil JR, Corbeil ME. Are we ready for mobile learning now? 2007 Mobile learning predictions revisited. Issues Inform Syst 2011; 12: 142-52.

Schilling K, Wiecha J, Polineni D, Khalil S. An interactive web-based curriculum on evidence-based medicine: design and effectiveness. Fam Med 2006; 38: 126-32.

Lai CY, Wu CC. Promoting Nursing Students’ Clinical Learning Through a Mobile e-Portfolio. Comput Informa Nurs 2016; 34: 535-43.

Masood A, Sheng B, Li P, Hou X, Wei X, Qin J, et al. Computer-Assisted Decision Support System in Pulmonary Cancer detection and stage classification on CT images. J Biomed Inform 2018, 117-28.

Murgu S, Rabito R, Lasko G, Jackson C, Mino-Kenudson M, Ettinger DS, et al. Impact of a Non-small Cell Lung Cancer Educational Program for Interdisciplinary Teams. Chest 2018; 153: 876-87.

Basch E, Pugh SL, Dueck AC, Mitchell SA, Berk L, Fogh S, et al. Feasibility of Patient Reporting of Symptomatic Adverse Events via the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) in a Chemoradiotherapy Cooperative Group Multicenter Clinical Trial. Int J Radiat Oncol Biol Phys 2017; 98: 409-18.

DuBenske LL, Gustafson DH, Shaw BR, Cleary JF. Web-based cancer communication and decision making systems: connecting patients, caregivers, and clinicians for improved health outcomes. Med Decis Making 2010; 30: 732-44.

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Published

2023-04-19

How to Cite

Kul, S., & Doğan, İlkay. (2023). Are Lung Cancer Publications Up-to-Date in terms of Advances in Statistics and Bioinformatics?. European Journal of Therapeutics, 24(S1), S57-S60. https://doi.org/10.5152/EurJTher.2018.1012

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Original Articles