Patricia Guyot1, Wei Cheng1,2, Gabriel Tremblay3, Ronda Copher3, Heather Burnett4, Xuan Li3, Charles Makin5. 1. Real World Strategy & Analytics, Mapi Group, 27 rue de la Villette, Lyon 69003, France. 2. The Knowledge Synthesis Group, Ottawa Hospital Research Institute, 501 Smyth Road, PO Box 201B, Ottawa, Ontario K1H 8L6, Canada. 3. Eisai, 155 Tice Boulevard, Woodcliff Lake, NJ 07677, USA. 4. Real World Strategy & Analytics, Mapi Group, 40 Court Street, Suite 410, Boston, MA 02108, USA. 5. RWE & Late Phase Research, ICON plc, 2100 Pennbrook Pkwy, North Wales, PA 19454, USA.
Abstract
AIM: For dichotomous outcomes, odds ratio (OR) is one of the usual summary measures of indirect treatment comparison. A corresponding number needed to treat (NNT) estimate may facilitate understanding of the treatment effect. METHODS: We show how to estimate NNT based on OR results of a matching adjusted indirect comparison. We also have derived the explicit formula of its 95% CIs by applying the delta method, and as an alternative, a simulation-based method. RESULTS: The method was applied in a case study example in radioiodine-refractory differentiated thyroid cancer (RR-DTC) patients, comparing lenvatinib to sorafenib. For every two RR-DTC patients treated with lenvatinib instead of sorafenib, one fewer would have progressed and for every eight RR-DTC patients treated with lenvatinib instead of sorafenib, one fewer would have died. CONCLUSION: Using NNT to summarize the results of a matching adjusted indirect comparison can help the clinicians to better understand the results in addition to OR.
AIM: For dichotomous outcomes, odds ratio (OR) is one of the usual summary measures of indirect treatment comparison. A corresponding number needed to treat (NNT) estimate may facilitate understanding of the treatment effect. METHODS: We show how to estimate NNT based on OR results of a matching adjusted indirect comparison. We also have derived the explicit formula of its 95% CIs by applying the delta method, and as an alternative, a simulation-based method. RESULTS: The method was applied in a case study example in radioiodine-refractory differentiated thyroid cancer (RR-DTC) patients, comparing lenvatinib to sorafenib. For every two RR-DTC patients treated with lenvatinib instead of sorafenib, one fewer would have progressed and for every eight RR-DTC patients treated with lenvatinib instead of sorafenib, one fewer would have died. CONCLUSION: Using NNT to summarize the results of a matching adjusted indirect comparison can help the clinicians to better understand the results in addition to OR.
Entities:
Keywords:
evidence synthesis; indirect treatment comparison; number needed to treat