COX REGRESSION IN HEALTH SCIENCES USING SPSS SOFTWARE

In this paper presents theoretical bases of the Cox regression as one of the most popular multidimensional methods of survival analysis. This method of analysis in most cases is used to determine the independent influence of potential risk factors on the rate of occurrence of the event under study during the time period studied. The practical example describes the principles of Cox proportional hazard analysis and the basic principles of interpreting the information received with the SPSS application statistical software package.

Keywords: survival analysis, survival, Cox regression analysis, proportionality of risks, SPSS.

Ekaterina E. Sharashova 1,

Kamila K. Kholmatova 2,

Maria A. Gorbatova 2, http://orcid.org/0000-0002-6363-9595

Andrej M. Grjibovski 2-5, http://orcid.org/0000-0002-5464-0498

 

1 Arctic University of Norway, Tromsø, Norway;

2 Northern State Medical University, Arkhangelsk, Russia;

3 Norwegian Institute of Public Health, Oslo, Norway;

4 International Kazakh-Turkish University, Turkestan, Kazakhstan;

5 North-Eastern Federal University, Yakutsk, Russia.

1.         Burdyak A.Y. Primenenie analiza «Analyz nastupleniya sobytiya (Event history analysis) s pomoshju paketa SPSS». [The application of the «event hystory analysis in SPSS»] SPERO. Sotsialnaya politika: ekspertiza, rekomendacii, obzory. [SPERO. Social politics: expertise, recommendations, reviews]. 2007. N 6. P. 189-202. [in Russian]

2.         Rumyancev P.O., Saenko V.A., Rumyanceva U.V., Chekin S.U. Statisticheskie metody analiza v klinicheskoi praktike. Chast 2: Analiz vyzhivaemosti i mnogomernaya statistica. [Statistical methods of analysis in clinical practice& Part 2: Survival analysis and multiple statistics]. Problemy endokrinologii [Problems of endocrinology]. 2009. N 6. P. 48-56. [in Russian]

3.         Kholmatova K.K., Grjibovski A.M. Primenenie analiza dozhitiya v zdravoohranenii  [The application of survival analysis in health sciences]. Nauka i zdravoohranenie [Science and Health Care] 2016. №5. рр. 5-28. [in Russian]

4.         Kholmatova K.K., Dvoryashina I.V. Prognosticheskoe znachenie urovnei glikemii, zaregistrirovannyh pri postuplenii, u pacientov s infarctom miokarda. [Prognostic value of admission glycaemia levels in patients with myocardial infarction]. Arhiv vnutrennei mediciny [Archive of internal medicine]. 2014. N 1. P. 25-29. [in Russian]

5.         Kholmatova K.K., Dvoryashina I.V., Supryadkina T.V. Vliyanie glikemii na rannij prognoz pacientov s infarktom miokarda bez saharnogo diabeta 2 tipa v anamneze [Influence of glycaemia on short-term prognosis of patients with myocardial infarction and without diabetes mellitus type 2 in anamnesis]. Kardiovaskulyarnaya terapiya I profilaktika [Cardiovascular therapy and prevention]. 2014. N 2. P. 29-34. [in Russian]

6.         Kholmatova K.K., Dvoryashina I.V., Supryadkina T.V. Razlichnye varianty narushenij uglevodnogo obmena i ih vliyanie na techenie infarcta miocarda u pacientov g. Arkhangelska. [Different glucose metabolism disorders and its influence on the myocardial infarction course in patients in Arkhangelsk]. Ekologiya cheloveka [Human ecology]. 2013. N 10. P.14-22. [in Russian]

7.         Kholmatova K.K., Dvoryashina I.V., Fomkina I.A., Supryadkina T.V. Prognosticheskoe znachenie soderzhaniya adiptscitokinov u ptscientov s infarctom miokarda I razlichnymi variantami narushenii uglevodnogo obmena. [Prognostic value of adipokines’ levels in patients with myocardial infarction and glucose metabolism disorders]. Sakharnyi diabet [Diabetes mellitus]. 2014. N 3. P. 90-95. [in Russian]

8.         Kholmatova K.K., Sharashova E.E., Gorbatova M.A., Grjibovski A.M. Primenenie mnozhestvennogo logisticheskogo regressionnogo analiza v zdravoohranenii s ispol'zovaniem paketa statisticheskikh programm SPSS [The application of multiple logistic regression analysis in health sciences using SPSS software]. Nauka i zdravookhranenie [Science & Healthcare] 2017. №4. С. 5-26. [in Russian]

9.         Sharashova E.E., Kholmatova K.K., Gorbatova M.A., Grjibovski A.M. Primenenie mnozhestvennogo lineinogo regressionnogo analiza v zdravookhranenii s ispol'zovaniem paketa statisticheskikh programm SPSS [The application of multiple logistic regression analysis in health sciences using SPSS software]. Nauka i zdravookhranenie [Science & Healthcare] 2017. №3. С. 5-31. [in Russian]

10.     Junkerov V.I., Grigoriev S.G. Matematiko-statisticheskaya obrabotka dannykh meditsinskikh issledovanii [Mathematical and statistical analysis of the medical research data]. SPb: VMedA, 2002. 266 p. [in Russian]

11.     Cox D. R. Regression models and life tables (with discussion). J. R. Statist. Soc., Series B. 1972. N 2. P. 187- 220.

12.     Foster J. Understanding and using advanced statistics. Foster J., Barkus M., Yavorsky C. London: SAGE Publications Ltd., 2006. 178 p.

13.     Hosmer JR. DW, Lemeshow S. Applied Survival Analysis; Regression Modeling of Time to Event Data. New York: John Wiley & Sons, 1999. 416 p.

14.     Kleinbaum D.G., Klein M. Survival analysis: a self-learning text (3rd ed.). New York, 2012. 591 p.

15.     Machin D., Cheung Y., Palmar M. Survival analysis: a practical approach (2nd ed.). New York, 2006. 267 p.

16.     NCSS statistical software. Cox regression: [site]. URL: http://ncss.wpengine.netdna-cdn.com/wp-content/themes/ncss/pdf/Procedures/NCSS/Cox_Regression.pdf

17.     Norusis M.J. SPSS 15.0 advanced statistical procedures companion. New Jersey, 2007. 418 p.

18.     Peat J., Barton B. Medical statistics: a guide to data analysis and critical appraisal (1st  ed.). NY: Blackwell Publishing, 2005. 324 p.

19.     Rao S.R., Schoenfeld D.A. Survival methods. Circulation. 2007. N 115. P. 109-113.

Statsoft. Survival / Failure Time Analysis: [site]. URL: http://www.statsoft.com/Textbook/Survival-Failure-Time-Analysis
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Bibliography link

Sharashova E.E., Kholmatova K.K., Gorbatova M.A., Grjibovski A.M. Cox regression in health sciences using spss software. Nauka i Zdravookhranenie [Science & Healthcare]. 2017, 6, pp. 5-27.


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