HAD5304H Operatons|Temporal Lobectomy

HAD5304H Operatons|Temporal Lobectomy
Questions 1. Construct a decision tree for two strategies: medical management and temporal lobectomy. Assume that the base case is a 35 year old with a life expectancy of 28 years (if treatment is unsuccessful). Successful treatment (seizure-free) extends life expectancy by 8 years. Use life years as the outcome. Construct the tree using all of the best practices in decision modeling. Fold back, report results and provide an interpretation (maximum 200 words) for your findings. Your interpretation must include clinical or policy implications of your findings. Save this tree as LASTNAME_1.TREX, substituting your last name for LASTNAME. [10 points] 2. Modify your tree in Question 1 to incorporate utilities. Fold back, report results and provide an interpretation (maximum 200 words) for your findings. Your interpretation must include clinical or policy implications of your findings. Make sure to compare your response to question 2 to what you observed in question 1. Save this tree as LASTNAME_2.TREX, substituting your last name for LASTNAME. [10 points] 3. Using your tree from Question 2: a. Perform a sensitivity analysis on the RR of disabling seizures with surgery, varying it from 0.3 to 0.9. Graph, report and provide an interpretation (maximum 200 words) for your findings. b. Perform a sensitivity analysis on the expected life years if seizure-free, varying this from 28 to 40 years. Graph, report and provide an interpretation (maximum 200 words) for your findings. Your interpretation must include clinical or policy implications of your findings. Paste the graphs into a word document. Do not submit separate graph files. [10 points] 4. While temporal lobectomy generally produces minimal measurable postoperative neurocognitive effects in patients with right temporal lobectomy, patients who undergo left temporal lobectomy may experience verbal memory loss. Modify your tree from Question 2 to assess temporal lobectomy in patients requiring left temporal lobectomy. Verbal memory loss can be predicted using a number of metrics. Assume the predicted degree of verbal memory loss is correct. a. For a patient with a predicted moderate memory loss, assume a quality of life penalty of 0.25 (i.e., decreasing the utility of surgery outcomes by 25%). Fold back, report results and provide an interpretation (maximum 200 words) for your findings. Your interpretation must include clinical or policy implications of your findings. b. Repeat your analysis for a patient with a predicted mild memory loss (assume a quality of life penalty of 0.1), and for a patient with a predicted severe memory loss (assume a quality of life penalty of 0.4). Fold back, report results and provide an interpretation (maximum 200 words) for your findings. Your interpretation must include clinical or policy implications of your findings. (maximum 200 words). c. Provide a graph that presents a one-way sensitivity analysis showing whether there is a threshold for the quality of life penalty for memory loss at which your recommendation (medical management or temporal lobectomy) changes. Graph, report and provide an interpretation (maximum 200 words) for your findings. Your interpretation must include clinical or policy implications of your findings. Save this tree as LASTNAME_3.TREX, substituting your last name for LASTNAME. Paste the graphs into a word document. Do not submit separate graph files. [12 points] 5. Using your tree from Question 4, perform a two-way sensitivity analysis on the RR of disabling seizures and the quality of life penalty for memory loss (mild, moderate, and severe). Provide a graph that presents a two-way sensitivity analysis showing all possible combinations (Up to 3 bonus points for using a table to show the three categories of memory loss). Graph, report and provide an interpretation (maximum 200 words) for your findings. Your interpretation must include clinical or policy implications of your findings. Paste the graphs into a word document. Do not submit separate graph files.
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