CLINICAL RESEARCH METHODS VISP356. MODULE LEADER: PROF A TOMLINSON B.Sc./B.Sc.(HONS) OPTOMETRY

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1 DIVISION OF VISION SCIENCES SESSION: 2006/2007 DIET: 1ST CLINICAL RESEARCH METHODS VISP356 LEVEL: MODULE LEADER: PROF A TOMLINSON B.Sc./B.Sc.(HONS) OPTOMETRY MAY 2007 DURATION: 2 HRS CANDIDATES SHOULD ATTEMPT FOUR QUESTIONS PLEASE READ THE QUESTIONS CAREFULLY Students for whom English is not their first language are permitted to use a Standard English/Foreign Language dictionary, e.g. French/English/English/French. Please ensure that the dictionary does not contain any notes or other materials and note that electronic dictionaries are not permissible MATERIALS TO Lined Examination Script Books BE SUPPLIED/ALLOWED: Unlined Examination Script Books Other Materials, e.g. Graph paper, statistical tables (please specify) formula sheets attached Page 1 of 8

2 1. a) Describe briefly each of the following concepts within the context of statistical data analysis: i) the p value. (3) ii) sample size estimation in design planning. (3) b) A study was to be conducted to compare corneal thickness measurements in dry eye and normal postmenopausal women, the latter providing an agematched control group. The study was designed to advise on the selection of postmenopausal women for corneal photoablation surgery. i) Two groups of women aged 51 to 55 were required to be selected. Within the proposed study, one of the variables to be measured was central corneal thickness, in μm. A mean difference of μm was thought by the investigators to be sufficient to indicate statistically significant difference in central corneal thickness between dry eye and normal postmenopausal women. Past comparable studies suggested a standard deviation estimate of μm could be assumed for central corneal thickness. The independent samples t test is to be carried out at the 5% significance level with power approximately 85%. Estimate the number of patients necessary for each planned study group. Comment on your answer. (4) ii) When the described study was run, data were also collected on tear break up time (TBUT), in seconds, before corneal thickness measurement. The investigators wished to assess if there was a difference in tear break up time between the dry eye and normal patient groups at baseline. The investigators were unsure whether to assess this effect through a parametric or nonparametric test. The SPSS statistical software package was used to create both parametric and nonparametric inferential data analysis output for the TBUT data (see Appendix A). Use the output provided to answer the following. a) Apply the parametric inference information to test, at the 1% significance level, whether there is sufficient evidence to suggest that TBUT differs between dry eye and normal postmenopausal women. State clearly the hypotheses being assessed and the practicality of the conclusion reached. (4) b) Apply the nonparametric inference information to conduct the same assessment as requested in (a) above. (4) c) Comment on the conclusions arrived at in (a) and (b) above. (2) Question 2 on next page / Page 2 of 8

3 2. a) A study, based on a two factor factorial design structure, was conducted into corneal sensation threshold, measured in millibars. Two factors, contact lens type and peripheral test location on the cornea, were assessed. For the contact lens type, patients were split into three groups: non-lens wearers, soft lens wearers and rigid gas permeable (RGP) lens wearers. For the test location factor, measurements were to be made at the temporal, medial and inferior corneal locations. The study was designed to assess if there was a link between these factors and the corneal sensation threshold measurement made on each subject s right eye at least 10 minutes after removal of the contact lens. Ten patients were randomly assigned to each factor-level combination. i) State and explain fully the response model appropriate for the described design. (2) ii) Specify the assumptions associated with the model provided in (i). (2) The SPSS statistical software package was used to create data analysis output for the collected corneal sensation threshold data (see Appendix B). Use the output provided to help answer the following. iii) Interpret the ANOVA output to decide whether there is sufficient evidence, at the 5% significance level, to suggest that contact lens type and peripheral test location interact in their effect on corneal sensation threshold. State clearly the hypotheses being assessed and the practicality of the conclusion reached. (4) iv) Based on the outcome to the analysis in (iii), what would you advise be the next steps in the data analysis? Justify your suggestions. (3) b) A study was conducted into the effect of exercise on pulsatile ocular blood flow and its link to intraocular pressure. The study participants represented a random sample of visually normal patients, evenly split by gender and aged between 24 and 25 years. Intraocular pressure (IOP, mmhg) and pulsatile ocular blood flow (POBF, μl/min) were measured by pneumotonometry before and immediately after exercise consisting of a 4-minute period of cycling at a constant rate of 80 rpm. Of interest to the investigators was assessment of the relationship between the change in IOP and change in POBF with exercise. The SPSS statistical software package was used to create data analysis output for these data (see Appendix C). Use the output provided to help answer the following. i) Over what range of values is it appropriate to use the fitted model, if proved statistically and practically appropriate? Give a reason for your answer. (1) ii) On next page. Page 3 of 8

4 Question 2 (continued) ii) Assess the validity of the suggestion that a linear relationship may exist between change in IOP and change in POBF. (3) iii) State the coefficient of determination and comment on its practical meaning. (2) iv) Use the provided predictions plot to assess the practicality of the linear model fitted to the relationship between change in IOP and change in POBF. (3) 3. Describe odds ratio and relative risk, the frequently used measures in clinical research studies. Indicate how these two measures differ (give an example). Describe the type of clinical research studies in which these two measures are frequently used. (20) 4. Describe the key measures of diagnostic test performance, sensitivity, specificity, predictive values and accuracy of the test. What are the factors which determine sensitivity and specificity and how do they differ from the values which are responsible for the computation of predictive values? What is required in the detection of a disease which occurs rarely in a population? What are required for a screening test and a diagnostic test, how do the requirements differ? Diagnostic tests are often used in combination, how are results combined and how does this effect the performance of the test? (20) Page 4 of 8

5 5. a) Two years ago, you measured the visual acuity of a patient using a logmar chart and recorded his performance in the following way (first entry corresponds to logmar acuity, second entry specifies the number of letters correctly identified): / / / / /6 Sketch a psychometric function of letter size versus percent correct letter identification for this patient. (4) b) How would you define this patient s visual acuity from this data? Justify your answer using the graph. (4) c) What is the equivalent Snellen acuity? (2) d) The patient returns today for a routine examination. As part of your clinical assessment, you wish to determine if the acuity today is different from his last visit. He can read: / / / / / /6 Add a sketch of the psychometric function of letter size versus percent correct letter identification for today s measurements to the graph in a). (4) e) Has there been a significant reduction in his visual acuity? Justify your answer. (6) Page 5 of 8

6 Appendix A [Question 1(b)] TBUT Group Dry eye Normal Group Statistics Std. Error N Mean Std. Deviation Mean Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means TBUT Equal variances assumed Equal variances not assumed F Sig. t df Sig. (2-tailed) Mean Difference Dry eye - Normal Std. Error Difference Ranks TBUT Group Dry eye Normal Total N Mean Rank Sum of Ranks Test Statistics b Mann-Whitney U Wilcoxon W Z Asymp. Sig. (2-tailed) Exact Sig. [2*(1-tailed Sig.)] a. Not corrected for ties. b. Grouping Variable: Group TBUT a Appendix B on next page / Page 6 of 8

7 Appendix B [Question 2(a)] Tests of Between-Subjects Effects: CST - corneal sensation threshold (millibars) Dependent Variable: CST Source Model LensType TestLocn LensType * TestLocn Error Total Type III Sum of Squares df Mean Square F Sig a a. R Squared =.827 (Adjusted R Squared =.808) Page 7 of 8

8 Appendix C [Question 2(b)] Change in POBF against change in IOP Change in POBF (micorlitres/min) Change in IOP (mmhg) Model Summary Model 1 Adjusted Std. Error of R R Square R Square the Estimate.901 a a. Predictors: (Constant), ChIOP Predicted and measured change in POBF Change in POBF (micorlitres/min) R Sq Linear = Change in IOP (mmhg) Page 8 of 8