Abstract
Cancer is largely a disease of aging with increasing incidence with age for most malignancies and the majority of cancer patients diagnosed after age 65. At the same time, aging is associated with a progressive increase in the number of major medical comorbid conditions that may complicate the disease course and increase treatment-related complications and their adverse consequences. Unfortunately, age restrictions in clinical trials have led to limited data on the special characteristics, comorbidities, and outcomes of older patients with cancer. Geriatric Oncology has emerged as a subdiscipline within oncology with a focus on clinical management and research related to cancer in the older patient. Topics in Geriatric Oncology studied in randomized or nonrandomized clinical studies including those captured in systematic evidence reviews and meta-analyses cover a broad range of subjects related to cancer in the elderly. In this chapter, the basic methodology for conducting high quality systematic reviews and evidence summaries including meta-analyses is summarized. Such studies range across areas of prevention and screening, diagnosis and staging, functional assessment including comprehensive geriatric assessment, cancer treatment, supportive care, and survivorship and end-of-life. Systematic reviews start with defining the specific question and then establishing the relevant clinical setting including the target patient population or problem, the exposure, prognostic factor or intervention, any relevant comparison(s), and clinically important outcomes. Subsequently, a rigorous explicit and transparent process of identifying, appraising, and selecting or excluding the relevant evidence is undertaken. The resulting evidence from the systematic review may then be summarized descriptively or, when appropriate, in the form of a formal meta-analysis. Later in the chapter, a summary of reported systematic reviews and/or meta-analyses related to Geriatric Oncology over the past two decades is presented and summarized. Finally, available tools for the conduct, analysis, quality appraisal, and reporting of systematic reviews and meta-analyses are provided for the reader interested in a better understanding of such systematic evidence reviews.
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References
Bland JM, Altman DG. Regression towards the mean. BMJ. 1994;308:1499.
Bossuyt PM, Reitsma JB, Bruns DE, et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. BMJ. 2003;326:41–4.
Bossuyt PM, Reitsma JB, Bruns DE, et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Fam Pract. 2004;21:4–10.
Bown MJ, Sutton AJ. Quality control in systematic reviews and meta-analyses. Eur J Vasc Endovasc Surg. 2010;40:669–77.
Burdett S, Stewart LA. A comparison of the results of checked versus unchecked individual patient data meta-analyses. Int J Technol Assess Health Care. 2002;18:619–24.
Buscemi N, Hartling L, Vandermeer B, et al. Single data extraction generated more errors than double data extraction in systematic reviews. J Clin Epidemiol. 2006;59:697–703.
CEBM. Critical appraisal tools. Centre for Evidence-Based Medicine, Oxford; 2007.
Deeks J. Systematic reviews of evaluations of diagnostic and screening tests. In: Egger M, Davey Smith G, Altman D, editors. Systematic reviews in health care: meta-analysis in context. London: BMJ Publishing Group; 2001a.
Deeks JJ. Systematic reviews in health care: systematic reviews of evaluations of diagnostic and screening tests. BMJ. 2001b;323:157–62.
Earle CC, Pham B, Wells GA. An assessment of methods to combine published survival curves. Med Decis Mak. 2000;20:104–11.
Eden J, Levit L, Berg A, et al., editors. Finding what works in health care: standards for systematic reviews. Washington, DC: National Academies Press; 2011.
Elamin MB, Flynn DN, Bassler D, et al. Choice of data extraction tools for systematic reviews depends on resources and review complexity. J Clin Epidemiol. 2009;62:506–10.
Fleming PS, Koletsi D, Pandis N. Blinded by PRISMA: are systematic reviewers focusing on PRISMA and ignoring other guidelines? PLoS One. 2014;9:e96407.
Horton J, Vandermeer B, Hartling L, et al. Systematic review data extraction: cross-sectional study showed that experience did not increase accuracy. J Clin Epidemiol. 2010;63:289–98.
Kho ME, Eva KW, Cook DJ, et al. The completeness of reporting (CORE) index identifies important deficiencies in observational study conference abstracts. J Clin Epidemiol. 2008;61:1241–9.
Lijmer JG, Mol BW, Heisterkamp S, et al. Empirical evidence of design-related bias in studies of diagnostic tests. JAMA. 1999;282:1061–6.
Lyman GH, Kuderer NM. The strengths and limitations of meta-analyses based on aggregate data. BMC Med Res Methodol. 2005;5:14.
Moher D, Cook DJ, Eastwood S, et al. Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement Quality of Reporting of Meta-analyses. Lancet. 1999;354:1896–900.
Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.
Olkin I, Sampson A. Comparison of meta-analysis versus analysis of variance of individual patient data. Biometrics. 1998;54:317–22.
Richardson WS, Wilson MC, Nishikawa J, et al. The well-built clinical question: a key to evidence-based decisions. ACP J Club. 1995;123:A12–3.
Shea BJ, Grimshaw JM, Wells GA, et al. Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews. BMC Med Res Methodol. 2007;7:10.
Steinberg KK, Smith SJ, Stroup DF, et al. Comparison of effect estimates from a meta-analysis of summary data from published studies and from a meta-analysis using individual patient data for ovarian cancer studies. Am J Epidemiol. 1997;145:917–25.
Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group. JAMA. 2000;283:2008–12.
Sylvester R, Collette L, Duchateau L. The role of meta-analyses in assessing cancer treatments. Eur J Cancer. 2000;36:1351–8.
Tierney JF, Clarke M, Stewart LA. Is there bias in the publication of individual patient data meta-analyses? Int J Technol Assess Health Care. 2000;16:657–67.
Tudur C, Williamson PR, Khan S, et al. The value of the aggregate data approach in meta-analysis with time-to-event outcomes. J R Stat Soc A Stat Soc. 2001;164:357–70.
Vamvakas EC. Meta-analyses of studies of the diagnostic accuracy of laboratory tests: a review of the concepts and methods. Arch Pathol Lab Med. 1998;122:675–86.
Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration. Epidemiology. 2007;18:805–35.
Viswanathan M, Ansari MT, Berkman ND, et al. Assessing the risk of bias of individual studies in systematic reviews of health care interventions. Methods guide for effectiveness and comparative effectiveness reviews. AHRQ Methods for Effective Health Care. Rockville; 2008.
von Elm E, Altman DG, Egger M, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Epidemiology. 2007;18:800–4.
Whiting P, Rutjes AW, Reitsma JB, et al. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3:25.
Whiting PF, Weswood ME, Rutjes AW, et al. Evaluation of QUADAS, a tool for the quality assessment of diagnostic accuracy studies. BMC Med Res Methodol. 2006;6:9.
Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529–36.
Willis BH, Quigley M. The assessment of the quality of reporting of meta-analyses in diagnostic research: a systematic review. BMC Med Res Methodol. 2011;11:163.
Zeng X, Zhang Y, Kwong JS, et al. The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta-analysis, and clinical practice guideline: a systematic review. J Evid Based Med. 2015;8:2–10.
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Lyman, G.H., Poniewierski, M.S. (2018). Research Methods: Systematic Reviews and Meta-Analysis in Geriatric Oncology. In: Extermann, M. (eds) Geriatric Oncology . Springer, Cham. https://doi.org/10.1007/978-3-319-44870-1_9-1
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DOI: https://doi.org/10.1007/978-3-319-44870-1_9-1
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