Sample size determination for logistic regression revisited

Demidenko, Eugene

doi:10.1002/sim.2771

Cited by 359 publications

(308 citation statements)

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“…According to the estimate of variables in the final model, the smallest sample was considered to be 70 cases and 70 controls. 22,23 The Project was approved by the institutional review board of the UFPR -Curitiba-Brazil (Nº 299. EXT.005/2009-03).…”

Section: Methodsmentioning

confidence: 99%

Oral acetylsalicylic acid and prevalence of actinic keratosis

Schmitt

Miot

2014

Rev. Assoc. Med. Bras.

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Section: Methodsmentioning

confidence: 99%

Oral acetylsalicylic acid and prevalence of actinic keratosis

Schmitt

Miot

2014

Rev. Assoc. Med. Bras.

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“…We determined odds ratio (OR) effect-size estimates for three levels (20%, 33%, 50%) of prevalence of candidate binary baseline characteristics [11,12]. Given a conservative lost-to-followup rate of 20% at 24 months and an alpha of 0.05, and assuming a failure rate of 20%, we aimed to enroll a minimum of 330 patients to have 80% power to detect ORs greater than 2.4, 2.2, and 2.1 for characteristics with 20%, 33%, or 50% prevalence, respectively, among patients having shoulder arthroplasty.…”

Section: Statistical Analysis Study Sizementioning

confidence: 99%

What Factors are Predictive of Patient-reported Outcomes? A Prospective Study of 337 Shoulder Arthroplasties

Matsen

Russ

et al. 2016

Clinical Orthopaedics &Amp; Related Research

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Background Although shoulder arthroplasties generally are effective in improving patients' comfort and function, the results are variable for reasons that are not well understood. Questions/Purposes We posed two questions: (1) What factors are associated with better 2-year outcomes after shoulder arthroplasty? (2) What are the sensitivities, specificities, and positive and negative predictive values of a multivariate predictive model for better outcome? Methods Three hundred thirty-nine patients having a shoulder arthroplasty (hemiarthroplasty, arthroplasty for cuff tear arthropathy, ream and run arthroplasty, total shoulder or reverse total shoulder arthroplasty) between August 24, 2010 and December 31, 2012 consented to participate in this prospective study. Two patients were excluded because they were missing baseline variables. Forty-three patients were missing 2-year data. Univariate and multivariate analyses determined the relationship of baseline patient, shoulder, and surgical characteristics to a ''better'' outcome, defined as an improvement of at least 30% of the maximal possible improvement in the Simple Shoulder Test. The results were used to develop a predictive model, the accuracy of which was tested using a 10-fold cross-validation. Results After controlling for potentially relevant confounding variables, the multivariate analysis showed that the factors significantly associated with better outcomes were American Society of Anesthesiologists Class I (odds ratio [OR], 1.94; 95% CI, 1.03-3.65; p = 0.041), shoulder problem not related to work (OR, 5.36; 95% CI, 2.15-13.37; p \ 0.001), lower baseline Simple Shoulder Test score (OR, 1.32; 95% CI, 1.23-1.42; p \ 0.001), no prior shoulder surgery (OR, 1.79; 95% CI, 1.18-2.70; p = 0.006), humeral head not superiorly displaced on the AP radiograph (OR, 2.14; 95% CI, 1.15-4.02; p = Each author certifies that his or her institution approved the human protocol for this investigation that all investigations were conducted in conformity with ethical principles of research, and that informed consent for participation in the study was obtained. OR, 4.47; 95% CI,; p \ 0.001). Neither preoperative glenoid version nor posterior decentering of the humeral head on the glenoid were associated with the outcomes. The model predictive of a better result was driven mainly by the six factors listed above. The area under the receiver operating characteristic curve generated from the crossvalidated enhanced predictive model was 0.79 (generally values of 0.7 to 0.8 are considered fair and values of 0.8 to 0.9 are considered good). The false-positive fraction and the true-positive fraction depended on the cutoff probability selected (ie, the selected probability above which the prediction would be classified as a better outcome). A cutoff probability of 0.68 yielded the best performance of the model with cross-validation predictions of better outcomes for 236 patients (80%) and worse outcomes for 58 patients (20%); sensitivity of 91% (95% CI, 88%-95%); specificity of ...

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“…(2) In logistic regression analysis, [31][32][33] the association between a binary response (eg, disease present or absent) and an exposure variable y is modeled as logit(P(z|y)) ¼ log(P(1|y)/P(0|y)) ¼ b 0 þ b yz y where P(z|y), z A {0,1}, is the conditional response probability, and b 0 and b yz are constants. The value of the effect parameter b yz is estimated by maximum likelihood estimation.…”

Section: Appendixmentioning

confidence: 99%

Dilution of candidates: the case of iron-related genes in restless legs syndrome

et al. 2012

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Restless legs syndrome (RLS) is a common multifactorial disease. Some genetic risk factors have been identified. RLS susceptibility also has been related to iron. We therefore asked whether known iron-related genes are candidates for association with RLS and, vice versa, whether known RLS-associated loci influence iron parameters in serum. RLS/control samples (n ¼ 954/1814 in the discovery step, 735/736 in replication 1, and 736/735 in replication 2) were tested for association with SNPs located within 4 Mb intervals surrounding each gene from a list of 111 iron-related genes using a discovery threshold of P ¼ 5 Â 10 À4 . Two population cohorts (KORA F3 and F4 with together n ¼ 3447) were tested for association of six known RLS loci with iron, ferritin, transferrin, transferrin-saturation, and soluble transferrin receptor. Results were negative. None of the candidate SNPs at the iron-related gene loci was confirmed significantly. An intronic SNP, rs2576036, of KATNAL2 at 18q21.1 was significant in the first (P ¼ 0.00085) but not in the second replication step (joint nominal P-value ¼ 0.044). Especially, rs1800652 (C282Y) in the HFE gene did not associate with RLS. Moreover, SNPs at the known RLS loci did not significantly affect serum iron parameters in the KORA cohorts. In conclusion, the correlation between RLS and iron parameters in serum may be weaker than assumed. Moreover, in a general power analysis, we show that genetic effects are diluted if they are transmitted via an intermediate trait to an end-phenotype. Sample size formulas are provided for small effect sizes. Keywords: restless legs syndrome; iron parameters; MEIS1 haplotype; power calculation; linear regression; logistic regression INTRODUCTIONRestless legs syndrome (RLS) 1 is a sensory-motor disorder characterized by an urge to move and unpleasant sensations in the lower limbs at rest. In Caucasians, RLS is present in up to 10% of the population. 2,3 Pregnancy, uremia, celiac disease, and iron deficiency are considered to be risk factors. 4 RLS also has a considerable heritability and is associated with multiple genetic risk factors. Genome-wide association studies 5-10 identified variants in six loci encompassing the genes MEIS1, BTBD9, MAP2K5/SKOR1, PTPRD, and TOX3/non-coding RNA.Aiming for the identification of further genetic risk factors of RLS, we addressed the apparent relation of RLS susceptibility to iron metabolism and iron availability 11 that has been explained by cerebral iron being crucial in the etiology of RLS. 12 We therefore tested the SNPs at the loci of a candidate set of genes known to be involved in iron metabolism for association with RLS. Vice versa, we asked whether RLS genes are involved in iron metabolism because the RLSassociated SNP rs3923809 at the BTBD9 locus has previously been reported to be associated with the serum level of ferritin in a study on RLS subjects and their relatives. 6

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Sample size determination for logistic regression revisited

Cited by 359 publications

References 23 publications

Oral acetylsalicylic acid and prevalence of actinic keratosis

Oral acetylsalicylic acid and prevalence of actinic keratosis

What Factors are Predictive of Patient-reported Outcomes? A Prospective Study of 337 Shoulder Arthroplasties

Dilution of candidates: the case of iron-related genes in restless legs syndrome

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