{"doi":"10.1093/pm/pnac045","title":"Predicting Treatment Response with Sensory Phenotyping in Post-Traumatic Neuropathic Pain","abstract":"OBJECTIVE: Currently available treatments for neuropathic pain are only modestly efficacious when assessed in randomized clinical trials and work for only some patients in the clinic. Induced-pain or gain-of-function phenotypes have been shown to predict response to analgesics (vs placebos) in patients with neuropathic pain. However, the predictive value of these phenotypes has never been studied in post-traumatic neuropathic pain. METHODS: Mixed-effects models for repeated measures were used to evaluate the efficacy of pregabalin vs placebo in subgroups with induced-pain phenotypes (i.e., hyperalgesia or allodynia) in data from a recent, multinational randomized clinical trial (N = 539) that identified phenotypic subgroups through the use of a structured clinical exam. RESULTS: The difference in mean pain score between the active and placebo groups (i.e., delta) after 15 weeks of treatment for the subgroup with hyperalgesia was -0.76 (P = 0.001), compared with 0.19 (P = 0.47) for the subgroup that did not have hyperalgesia. The treatment-by-phenotype interaction, which tests whether subgroups have statistically different treatment responses, was significant (P = 0.0067). The delta for the subgroup with allodynia was -0.31 (P = 0.22), compared with -0.30 (P = 0.22) for the subgroup that did not have allodynia (treatment-by-phenotype interaction P = 0.98). CONCLUSIONS: These data suggest that hyperalgesia, but not allodynia, predicts response to pregabalin in patients with chronic post-traumatic neuropathic pain. This study extends the growing data supporting the utility of induced-pain phenotypes to predict response to analgesics in post-traumatic neuropathic pain. Sensory phenotyping in large, multisite trials through the use of a structured clinical exam has the potential to accelerate the development of new analgesics and improve the generalizability of clinical trial results.","journal":"Pain Medicine","year":2022,"id":289851,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9583,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":818049,"name":"Michael B. Sohn","orcid":"0000-0002-4981-8351","position":1,"is_corresponding":false},{"id":972388,"name":"Rachel De Guzman","orcid":null,"position":2,"is_corresponding":false},{"id":972389,"name":"Maria E. Frazer","orcid":null,"position":3,"is_corresponding":false},{"id":972390,"name":"Valerie F. Chiodo","orcid":null,"position":4,"is_corresponding":false},{"id":334932,"name":"Sonia Sharma","orcid":"0000-0002-1887-7420","position":5,"is_corresponding":false},{"id":938104,"name":"Paul Geha","orcid":"0000-0002-0537-7216","position":6,"is_corresponding":false},{"id":250033,"name":"John D. Markman","orcid":"0000-0001-6296-8998","position":7,"is_corresponding":false},{"id":292130,"name":"Jennifer S. Gewandter","orcid":"0000-0001-7938-6775","position":0,"is_corresponding":true}],"reference_count":21,"raw_metadata":null,"created_at":"2026-07-19T00:30:26.667578Z","pmid":"35312012","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":[]}