1. SHAN LI & HABIB KOUSSE OUTCOMES OF ORAL CARE KITS ON ORAL HEALTH FOR PATIENTS AT RISK FOR DEVELOPING ORAL MUCOSITIS

2. BACKGROUND Oral mucositis describes inflammation of oral mucosa resulting from chemotherapeutic agents or ionizing radiation. It is the most distressing side effect from treatment of cancer by chemotherapy. Oral care/rinses is one of the effective strategies to prevent or treat oral mucositis.

3. OBJECTIVE OF THE STUDY Comparing the effects of Pre and Post implementation of oral care kits on chemotherapy treated patients. Groups: Pre = July 2009 to June 2010 Post = July 2010 to June 2011

4. INFORMATION ABOUT ORIGINAL DATA Oral mucositis assessment Total Score “0-16” “0”=Normal Documented on admission and then at least twice a day. Missing data exists.

5. GRAPH PRODUCED BY LAURA AND GRACE BASED ON THE ORIGINAL DATA COLLECTED

6. FILTERING THE DATA Criteria to filter the data set: (1) Want two assessments for a patient on each day. (2) Ideal record time would be 8 am and 8 pm. (3) If there is only one assessment, take it at whatever time. (4) If there are more than two assessment, take the two closest to 8 am and 8 pm. Patient NumRecords NumMissing value Pre11330Yes Post12386Yes

7. GRAPH OF ORAL MUCOSITIS DEVELOPMENT (FILTERED DATA) Slight change in mean scores for the Post Implementation group.

8. GRAPH OF ORAL MUCOSITIS DEVELOPMENT (WITH EFFECT OF DAY 0 REMOVED)

9. T-TEST RESULTS FOR TREATMENT EFFECT PER DAY ( DAY 1 TO DAY 16) Day 123456 78 F-stat 1.610 0.21 3.392.831.75 4.645.59 P-value 0.218610.65590.08130.10780.2004 0.04420.0289 Day 910111213141516 F-stat 2.590.00.951.750.611.271.4810.02 P-value 0.12381.00.34260.20110.44520.27440.24000.0053

10. T-TEST RESULTS FOR TREATMENT EFFECT PER DAY ( DAY 1 TO DAY 16) CONT’D Except for days 7, 8, 16 all the t-tests are non significant at 0.05. For an appropriate analysis, we need to take into account multiple comparison and use bonferroni adjustment to conclude about the t-tests.

11. REPEATED MEASURES Take measurements on the same subject over time. The measurements have a temporal order and are clustered. Methods dealing with repeated measures (1) Multivariate Analysis (2) Univarate summery of the data for each subject (3) Mixed-effects model and ANOVA

12. (1) MULTIVARIATE ANALYSIS

13. PRE IMPLEMENTATION GROUP Individual oral mucositis development curve for the pre implementation group.

14. POST IMPLEMENTATION GROUP Individual oral mucositis development curve for the post implementation group.

15. (2) MIXED-EFFECTS MODEL AND ANOVA Random effect for each subject This random effect intereacts with all repeated- measures effects

16. SAS code and output (2) MIXED-EFFECTS MODEL AND ANOVA

17. CONCLUSIONS There is no significant difference for the Pre and Post treatments in preventing oral mucositis.