Erupción acneiforme por inhibidores del receptor de crecimiento epidérmico

Lagrán, Z. Martínez de; Ratón, Juan Antonio; Lasa, Olatz; Acebo, Elvira; Díaz‐Pérez, J.L.

doi:10.1016/s0001-7310(05)73110-0

Cited by 18 publications

(7 citation statements)

References 12 publications

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“…To compare the timing of online ADR reports to initial ADR reports in the literature, we looked at both common and rare events associated with our target drugs. Papulopustular (ie, acneiform) rash and fingernail changes are well-reported ADRs associated with erlotinib and were first described in published case reports in September 2005 [41] and September 2006 [42], respectively. Inspire posts for these reactions appeared 5 and 3 months in advance of publication, respectively.…”

Section: Resultsmentioning

confidence: 99%

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection

Nikfarjam¹,

Ransohoff²,

Callahan³

et al. 2019

JMIR Public Health Surveill

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Background Adverse drug reactions (ADRs) occur in nearly all patients on chemotherapy, causing morbidity and therapy disruptions. Detection of such ADRs is limited in clinical trials, which are underpowered to detect rare events. Early recognition of ADRs in the postmarketing phase could substantially reduce morbidity and decrease societal costs. Internet community health forums provide a mechanism for individuals to discuss real-time health concerns and can enable computational detection of ADRs. Objective The goal of this study is to identify cutaneous ADR signals in social health networks and compare the frequency and timing of these ADRs to clinical reports in the literature. Methods We present a natural language processing-based, ADR signal-generation pipeline based on patient posts on Internet social health networks. We identified user posts from the Inspire health forums related to two chemotherapy classes: erlotinib, an epidermal growth factor receptor inhibitor, and nivolumab and pembrolizumab, immune checkpoint inhibitors. We extracted mentions of ADRs from unstructured content of patient posts. We then performed population-level association analyses and time-to-detection analyses. Results Our system detected cutaneous ADRs from patient reports with high precision (0.90) and at frequencies comparable to those documented in the literature but an average of 7 months ahead of their literature reporting. Known ADRs were associated with higher proportional reporting ratios compared to negative controls, demonstrating the robustness of our analyses. Our named entity recognition system achieved a 0.738 microaveraged F -measure in detecting ADR entities, not limited to cutaneous ADRs, in health forum posts. Additionally, we discovered the novel ADR of hypohidrosis reported by 23 patients in erlotinib-related posts; this ADR was absent from 15 years of literature on this medication and we recently reported the finding in a clinical oncology journal. Conclusions Several hundred million patients report health concerns in social health networks, yet this information is markedly underutilized for pharmacosurveillance. We demonstrated the ability of a natural language processing-based signal-generation pipeline to accurately detect patient reports of ADRs months in advance of literature reporting and the robustness of statistical analyses to validate system detections. Our findings suggest the important contributions that social health network data can play in contributing to more comprehensive and timely pharmacovigilance.

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Section: Resultsmentioning

confidence: 99%

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection

Nikfarjam¹,

Ransohoff²,

Callahan³

et al. 2019

JMIR Public Health Surveill

View full text Add to dashboard Cite

show abstract

“…Sólo los casos graves (grados 3 o 4) que no conseguían Tiempo hasta aparición de la sintomatologíva control de los síntomas con el tratamiento estándar, eran derivados a las consultas del servicio de dermatología. Con menor frecuencia se presentó: xerosis en 10 pacientes (23,3%) con una mediana de días de aparición de 40 (20-56); fisuras en manos y pies en tres pacientes (7%), que aparecieron tras una mediana de 28 (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35) días; trastornos ungueales en dos pacientes tras una media de 42 (35-49) días (fig. 2).…”

Section: Resultsunclassified

“…El manejo adecuado de la toxicidad, por tanto, ayudará a maximizar el beneficio y minimizar los efectos negativos sobre el curso del tratamiento y, por tanto, mejorar de calidad de vida del paciente 5,9 . Desde que Busam et al 18 describieran por primera vez la toxicidad cutánea secundaria al tratamiento con anti-EGFR, se publican numerosos trabajos [19][20][21][22][23] que describen la aparición de casos anecdóticos. Walon et al 20 ya proponían en el año 2003 la inclusión del cetuximab en la lista de medicamentos susceptibles de inducir erupción acneiforme a propósito de 2 casos.…”

Section: Fisuras Paroniquiaunclassified

Toxicidad cutánea asociada a cetuximab en cáncer colorrectal metastásico

Rodriguez-Murphy

Villanueva-Herraiz

Ortega-García

et al. 2011

Farmacia Hospitalaria

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“…Papulopustular (acneiform) rash and nail-finger changes are well-reported ADRs associated with erlotinib and were first described in published case reports in September 2005 [31] and September 2006 [32], respectively. Inspire posts for these reactions appeared 5 and 3 months in advance of publication, respectively.…”

Section: Adrs Are Described In Internet Forums Prior To Published Repmentioning

confidence: 99%

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection (Preprint)

Nikfarjam¹,

Ransohoff²,

Callahan³

et al. 2018

Preprint

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Importance: Adverse drug reactions (ADRs) occur in nearly all patients on chemotherapy, causing morbidity and therapy disruptions. Detection of such of ADRs is limited in clinical trials, which are underpowered to detect rare events. Early recognition of ADRs in the post-marketing phase could substantially reduce morbidity and decrease societal costs. Internet community health forums provide a mechanism for individuals to discuss real-time health concerns and can enable computational detection of ADRs.Objective: To identify cutaneous ADR signals in social health networks and compare the frequency and timing of these ADRs to clinical reports in the literature. Design:We present a natural language processing (NLP) based ADR signal generation pipeline based on patient posts on internet social health networks. We identify user posts from Inspire health forum related to two chemotherapy classes: erlotinib, an epidermal growth factor receptor inhibitor, and nivolumab and pembrolizumab, immune checkpoint inhibitors. We extract mentions of ADRs from unstructured content of patient posts. We then perform population-level association analyses and time-to-detection analyses.Results: Our system detected ADRs from patient reports with high precision (0.90) and at frequencies comparable to those documented in the literature, but an average of 7 months ahead of their literature reporting. Known ADRs associated with higher proportional reporting ratios compared to negative controls, demonstrating the robustness of our analyses. Additionally, we discovered the novel ADR of hypohidrosis reported by 23 patients in erlotinib related posts; this ADR was absent from 15 years of literature on this medication and we recently reported the finding in a clinical oncology journal. Conclusions and relevance:Several hundred million patients report health concerns in social health networks, yet this information is markedly underutilized for pharmacosurveillance. We demonstrate the ability of an NLP-based signal generation pipeline to accurately detect patient reports of ADRs months in advance of literature reporting, and the robustness of statistical analyses to validate system detections. Our findings suggest the important contributions that social health network data can play in contributing to more comprehensive and timely pharmacovigilance.

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Erupción acneiforme por inhibidores del receptor de crecimiento epidérmico

Cited by 18 publications

References 12 publications

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection

Toxicidad cutánea asociada a cetuximab en cáncer colorrectal metastásico

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection (Preprint)

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