Literature DB >> 26831427

Selection bias: Selection of controls as a critical issue in the interpretation of results in a case control study.

Anjali Mahajan1.   

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Year:  2015        PMID: 26831427      PMCID: PMC4774075          DOI: 10.4103/0971-5916.174574

Source DB:  PubMed          Journal:  Indian J Med Res        ISSN: 0971-5916            Impact factor:   2.375


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Sir This is with reference to an article on the effect of oral hypoglycaemic agents (OHA) on bone metabolism in patients with type 2 diabetes mellitus (T2DM) published recently1. The authors have conducted a case-control study to evaluate the effect of various OHA on bone mineral density (BMD) in patients with T2DM. They have concluded that the use of OHA for a period of three years or more does not significantly affect the BMD in patients with T2DM1. However, there are a few methodological issues that may significantly affect the interpretation of study results and hence raise a question on the validity and the generalisability of the results obtained in the study. Firstly, if one enrols controls from a particular hospital within the geographic area, one would have to consider whether the controls were inherently more or less likely to have the exposure of interest. This was missing in the present study with total absence of exposure in the control group, since the controls chosen were healthy hospital employees who were least likely to take oral hypoglycaemic drugs which was the exposure variable in the study. In this study, 41 age- and gender-matched apparently healthy individuals chosen from hospital staff and employees were included as controls1. The selection of an appropriate comparison group is a critical issue in the design of case-control studies. The controls must be selected to represent not the entire non diseased population but the population of individuals who would have been identified and included as cases had they developed the disease. If so, they would not provide an accurate estimate of the exposure distribution of the source population, and selection bias would result. The crucial requirement is that the controls should be as comparable to the source population of the cases as possible and that any exclusions or restrictions made in the identification of cases apply equally to both the groups. Secondly, matching addresses the issue of confounding in the design stage of the case-control study. In the present study, controls were matched for age and sex. It is advisable that if matching is used, matched analysis must be used to take advantage of matching. If matching is done appropriately but not taken into account in analysis, the odds ratio will be biased towards the null. Lastly under the methodology section, the authors have mentioned that the study design chosen is cross-sectional and later it becomes evident that they have selected cases and controls. The cross-sectional study is categorized under the descriptive epidemiological study design strategy whereas case-control study is observational analytical study23.
  1 in total

1.  Effect of oral hypoglycaemic agents on bone metabolism in patients with type 2 diabetes mellitus & occurrence of osteoporosis.

Authors:  B Siddhartha Kumar; A Ravisankar; Alladi Mohan; D Prabath Kumar; D T Katyarmal; Alok Sachan; K V S Sarma
Journal:  Indian J Med Res       Date:  2015-04       Impact factor: 2.375

  1 in total
  4 in total

1.  Oral health-related quality of life in caregivers of individuals with Cerebral Palsy: a case-control study.

Authors:  É da S L Alvarenga; A M Silva; T A E da Silva; R F de Araújo; R R Prado Júnior; R F Mendes
Journal:  Eur Arch Paediatr Dent       Date:  2019-08-30

Review 2.  Vascular and haemodynamic issues of brain ageing.

Authors:  Lucy Beishon; Rebecca H Clough; Meeriam Kadicheeni; Tamara Chithiramohan; Ronney B Panerai; Victoria J Haunton; Jatinder S Minhas; Thompson G Robinson
Journal:  Pflugers Arch       Date:  2021-01-13       Impact factor: 3.657

Review 3.  Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation.

Authors:  Ernesto S Nakayasu; Marina Gritsenko; Paul D Piehowski; Yuqian Gao; Daniel J Orton; Athena A Schepmoes; Thomas L Fillmore; Brigitte I Frohnert; Marian Rewers; Jeffrey P Krischer; Charles Ansong; Astrid M Suchy-Dicey; Carmella Evans-Molina; Wei-Jun Qian; Bobbie-Jo M Webb-Robertson; Thomas O Metz
Journal:  Nat Protoc       Date:  2021-07-09       Impact factor: 17.021

4.  Authors' response.

Authors:  B S Kumar; A Ravisankar; A Mohan; D P Kumar; D T Katyarmal; A Sachan; K V S Sarma
Journal:  Indian J Med Res       Date:  2015-12       Impact factor: 2.375

  4 in total

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