{"doi":"10.1016/j.jclinepi.2005.08.005","title":"An unadjusted NNT was a moderately good predictor of health benefit","abstract":null,"journal":"Journal of Clinical Epidemiology","year":2006,"id":670770,"datarank":0.515098080672772,"base_score":3.4339872044851463,"endowment":3.4339872044851463,"self_citation_contribution":0.515098080672772,"citation_network_contribution":0.0,"self_endowment_contribution":0.515098080672772,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":30,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":272520,"name":"George Tomlinson","orcid":"0000-0002-9328-6399","position":1,"is_corresponding":false},{"id":1752236,"name":"Lisa Chodirker","orcid":null,"position":2,"is_corresponding":false},{"id":1752238,"name":"Nassi Figdor","orcid":null,"position":3,"is_corresponding":false},{"id":1752240,"name":"Mark Uster","orcid":null,"position":4,"is_corresponding":false},{"id":683411,"name":"Gary Naglie","orcid":"0000-0002-6274-0894","position":5,"is_corresponding":false},{"id":1752242,"name":"Murray D. Krahn","orcid":null,"position":6,"is_corresponding":false},{"id":1752234,"name":"Christopher A.K.Y. Chong","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"An unadjusted NNT was a moderately good predictor of health benefit","abstract":"<h4>Background and objective</h4>Whether the number needed to treat (NNT) is sufficiently precise to use in clinical practice remains unclear. We compared unadjusted NNTs to quality-adjusted life years (QALYs) gained, a more comprehensive measures of health benefit.<h4>Study design and setting</h4>From a subset (n = 65) of a dataset of 228 cost-effectiveness analyses, we compared how well NNTs predicted clinically important QALY gains using correlation analysis, multivariable models and receiver-operator curve (ROC) analysis.<h4>Results</h4>NNT was inversely correlated with QALY gains (P < .001); this relationship was affected by quality of life and life-expectancy gains of treatment (P <or= .04). The NNT is a moderately accurate predictor of treatments that provide large health benefits (area under ROC 0.74-0.81). For ruling out therapies with low QALY gains (threshold <or=0.125 to <or=0.5 QALYs), an NNT >15 had a sensitivity of 82% to 100%. For ruling in therapies with high QALY gains (threshold >or=0.125 to >or=0.5 QALYs), an NNT <or=5 had a specificity of 77%.<h4>Conclusion</h4>Using NNT thresholds of <or=5 and >15 to rule in and out therapies with large QALY gains may provide general guidance regarding the magnitude of health benefit.","is_dataset_classified":null,"base_score":3.4339872044851463,"endowment":3.4339872044851463,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"16488352","pmcid":null,"openalex_id":"https://openalex.org/W2046368309","authors":[],"funders":[],"total_grants":0,"fwci":4.6888,"citation_percentile":0.94708413,"influential_citations":0,"citation_trend":[{"year":2014,"count":1},{"year":2016,"count":1},{"year":2017,"count":3},{"year":2020,"count":4},{"year":2021,"count":3},{"year":2022,"count":7},{"year":2023,"count":2},{"year":2024,"count":2},{"year":2025,"count":2}],"oa_status":"closed","license":"https://www.elsevier.com/tdm/userlicense/1.0/","oa_locations":[{"url":"https://api.elsevier.com/content/article/PII:S0895435605002969?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S0895435605002969?httpAccept=text/plain","host_type":"publisher"},{"url":"https://doi.org/10.1016/j.jclinepi.2005.08.005","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/16488352","host_type":"repository"}],"fields_of_study":["Health Systems, Economic Evaluations, Quality of Life","Palliative Care and End-of-Life Issues","Economic and Financial Impacts of Cancer","Cost-Benefit Analysis","Evidence-Based Medicine","Humans","Insurance Benefits","Life Expectancy","Multivariate Analysis","Quality of Life","Quality-Adjusted Life Years","ROC Curve","Sample Size","Sensitivity and Specificity","Treatment Outcome"],"mesh_terms":["Cost-Benefit Analysis","Humans","Insurance Benefits","Life Expectancy","Quality of Life","ROC Curve","Sensitivity and Specificity","Multivariate Analysis","Treatment Outcome","Sample Size","Quality-Adjusted Life Years","Evidence-Based Medicine"],"keywords":["Medicine","Number needed to treat","Internal medicine","Confidence interval","Relative risk"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-15T23:45:46.131898Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}