The importance of the chosen statistical methods in medical research: study over modelling in estimation superficial varicose vein risk factors in young male population

Abstract

Objective: To clarify the under which conditions univariate analysis is insufficient and the importance of multiple logistic regression in medical research is the primary objective. For this purpose, lower extremity superficial venous risk factors were selected as a model in a young male population retrospectively planned.
Material and Method: All patients who presented to the General Surgery Clinic of 29 Mayıs State Hospital with symptoms of pruritus, edema, leg pain and swelling between May 30, 2016 and January 1, 2019 were retrospectively analyzed for this study.
Results: The results of univariate analysis showed that the development of varicose veins was significantly higher in terms of variables than in the control group. Family history [34 (61.8%) vs. 21 (38.2%)], p<0.008), smoking [37 (59.7%) and 25 (40.3), p<0.04], long-term standing, respectively [90 (53.6%) vs. 78 (46.4%), p<0.01], constipation [64 (55.2%) vs. 52 (44.8%), p<0.001] and the urban lifestyle [49 (56.7%) - 22 ( 43.3), p<0.04] were found to be effective on the development of varicose veins. However, when we do binary logistic regression for important univariate results; We found different results in terms of risk factors of varicose veins. The results showed that family history, smoking, long standing and constipation contributed to the development of varicose veins [(61.8% vs. 38.2%, AOR: 2.62 (1.35, 5.07), p (0.04)], [(59.7% vs. 40.3%, AOR: 2.08 (1.13, 3.8) p<0.02)], [(53.6%) 46.4%, AOR: 1.83 (1.06, 3.16) p<0.03)], [(55.2% and 44.8%) AOR: 1.74 (1.03, 2.92) p<0.04) ]. On the other hand, urban lifestyle was found to be insignificant [(56.7% and 43.3%, AOR: 1.73 (0.96, 3.15) p<0.07)*].
Conclusion: In cases where there is more than one independent variable affecting the dependent variable; In determining how and in what way the dependent variable is affected by independent variables; multiple logistic regression tests are more successful than univariate analysis. False or incomplete statistical studies selected in medical research may lead to very important false clinical interpretations.

Keywords

• Statistical and mathemical methods,medical research,modelling in estimation

Project Number

Yoktur

Tıbbi araştırmalarda seçilen istatistiksel yöntemlerin önemi: genç erkek popülasyonda yüzeysel variköz ven risk faktörlerinin kestirimi üzerine modelleme çalışması

Abstract

Amaç: Hangi koşullar altında tek değişkenli analizin yetersiz olduğunu ve tıbbi araştırmalarda multipl lojistik regresyonun önemini açıklığa kavuşturmak birincil amaçtır. Bu amaçla retrospektif olarak planlanan genç erkek popülasyonda alt ekstremite yüzeysel venöz risk faktörleri model olarak seçildi.
Gereç ve Yöntem: Bu çalışma için 30 Mayıs 2016-1 Ocak 2019 tarihleri arasında 29 Mayıs Devlet Hastanesi Genel Cerrahi Kliniği’ne kaşıntı, ödem, bacak ağrısı ve şişlik gibi semptomları olan tüm hastalar retrospektif olarak incelendi.
Bulgular: Tek değişkenli analiz sonuçları, variköz venlerin gelişiminin, değişkenler açısından kontrol grubundan anlamlı derecede yüksek olduğunu göstermiştir. Sırasıyla, aile öyküsü [34 (%61,8) vs. 21 (%38,2)], p<0,008), sigara içme [37 (%59,7) ve 25 (%40,3), p<0,04], uzun süreli [90 (%53,6) 78’e karşı (%46,4), p<0,01], kabızlık [64 (%55,2) - 52 (% 44,8), p<0,001] ve kentsel yaşam tarzı [49 (%56,7) - 22 (%43,3), p<0,04], varikoz venlerinin gelişimi üzerine etkili bulunmuştur. Oysa, önemli tek değişkenli sonuçlar için ikili lojistik regresyonunu yaptığımızda; Variköz venlerin risk faktörleri açısından farklı sonuçlar saptadık; Sonuçlar aile öyküsünün, sigara içmenin, uzun süre ayakta durmanın ve kabızlığın variköz venlerin gelişiminde katkıda bulunduğunu ortaya koydu [(%61,8’e karşı %38,2, AOR: 2,62 (1,35 ve 5,07), p<0,04))], [(%59,7’ye karşı %40,3, AOR: 2,08 (1,13 ve 3,8) p<0,02)], [(%53,6’a karşı %46,4, AOR: 1,83 (1,06 ve 3,16) p<0,03)], [(%55,2 ve %44,8) AOR: 1,74 (1,03 ve 2,92) p<0,04)]. Öte yandan, kentsel yaşam tarzı ise önemsiz bulundu [(%56,7 ve %43,3, AOR: 1,73 (0,96 ve 3,15) p<0,07)*].
Sonuç: Bağımlı değişkeni etkileyen birden fazla bağımsız değişken olduğu durumlarda; bağımlı değişkenin bağımsız değişkenlerden nasıl ve ne şekilde etkilendiğinin tespitinde; çoklu lojistik regresyon testleri, tek değişkenli analizden daha başarılıdır. Tıbbi araştırmalarda seçilen yanlış veya eksik istatistiksel çalışmalar çok önemli yanlış klinik yorumlara neden olabilir.

Keywords

• İstatistiksel ve matematiksel yöntemler,tıbbi araştırma,kestirimde modelleme

Supporting Institution

Yoktur

Project Number

Yoktur

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