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Enregistrement W2974872597 · doi:10.1182/blood-2018-99-113515

Evaluation of Unexplained Lymphadenopathy and Suspected Lymphoma in a Lymphoma Rapid Diagnostic Clinic

2018· article· en· W2974872597 sur OpenAlexaffabout
Shannon Nixon, Manjula Maganti, Ksenia Bezverbnaya, John Kuruvilla, Anca Prica, Robert Kridel, Vishal Kukreti, Patrick Gullane, Michael Reedijk, Melania Pintilie, Michael Crump

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphadenopathy Diagnosis and Analysis
Établissements canadiensPrincess Margaret Cancer CentreUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineMedical diagnosisLymphomaLymph nodeRetrospective cohort studyBiopsyExact testFollicular lymphomaRadiologySurgeryInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Lymphomas often present a diagnostic challenge, leading to delays in obtaining a definitive diagnosis. For some lymphomas, a delay in diagnosis can negatively influence outcomes of therapy and result in a shorter duration of remission. Patients are often referred for evaluation with lymphoma diagnosis based on cytology from fine needle aspiration (FNA), whereas excisional or core lymph node biopsy is required for definitive diagnosis. We established a nurse practitioner-led Lymphoma Rapid Diagnostic Clinic (LRDC) with the goal of reducing wait times to diagnosis and initiation of treatment. Program development included surgical and interventional radiology engagement, and dedicated operating room time for excisional lymph node biopsies. We conducted a retrospective chart review to describe the initial 30-month experience of the LRDC. Results were compared to time periods before implementation of the clinic to determine program impact, and identify areas for quality improvement. Methods: All patients referred to LRDC at Princess Margaret Cancer Centre (PM), part of University Health Network (UHN), with suspicion of lymphoma from June 1, 2015 to Nov 30, 2017 were evaluated. Patients were excluded if they arrived in clinic with confirmed diagnosis of lymphoma or declined further LRDC evaluation. Patient symptoms and relevant laboratory/imaging findings were collected to identify patterns of presentation and predictive factors for benign diagnoses. Time from initial consultation to diagnosis and treatment were compared to patients diagnosed with lymphoma by surgical, medical, or oncology services at UHN in 2008 and 2012. Statistical significance was investigated using Fisher Exact test for categorical variables, and non-parametric Wilcoxon rank sum test for continuous data. Statistical significance level was chosen at a 2-sided p-value of 0.05 or less. Results: Of 129 patients referred to LRDC with suspected lymphoma, 126 were included in the analysis. Median age was 55yrs (range 18- 95yrs), and 67 patients (53%) were female. Thirty-nine patients had non-diagnostic FNA and/or core biopsies at initial assessment. Twenty-five had a prior cancer diagnosis, 30 presented with B symptoms and 57 had palpable enlarged lymph nodes (Table 1). To obtain a definitive diagnosis, 93 patients had biopsies (46 image-guided cores, 37 excisional, 6 FNA, 4 bone marrow); 13 patients received a diagnosis after pathology review, 4 via peripheral blood flow cytometry, and 16 following other clinical or serologic/imaging investigations. Following evaluation, 66 patients (52%) had confirmation of a diagnosis of lymphoma (34 indolent, 18 aggressive, 14 Hodgkin lymphoma (HL)), 2 had acute leukemia, 14 had metastatic cancer, and 44 had non-malignant diagnoses (Table 2). Median time from initial assessment to lymphoma diagnosis was 16 days (interquartile range 9-24 days) for the patients assessed in LRDC and 28 days (interquartile range 19-48 days) for historical controls (p <0.001). Median time from initial LRDC assessment to treatment for aggressive lymphomas and HL was 29 days (interquartile range 21-43 days) compared to 48 days (interquartile range 28-78 days) for historical controls (p= <0.001). The total number of biopsies obtained before diagnosis was significantly fewer for patients assessed in LRDC compared to historical controls (p<0.001, Fisher's exact test). By univariable analysis, lymph node size >3.4 cm and presence of mediastinal or abdominal adenopathy increased the likelihood of a diagnosis of malignancy, while younger age, being a non-smoker, and prior rheumatologic condition were associated with a non-malignant diagnosis. In multivariable analysis, lymph node size, age and prior rheumatologic diagnosis remained significant. Presence of B symptoms was not predictive. Conclusion: Establishing the nurse practitioner-led LRDC was effective in shortening time to diagnosis and treatment, and reduced the number of biopsies required for definitive diagnosis of lymphoma. Younger age, smaller lymph node size and prior rheumatologic disorder reduced the likelihood of a cancer diagnosis in our patient population. Disclosures Kuruvilla: Princess Margaret Cancer Foundation: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy; Lundbeck: Honoraria; Seattle Genetics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Karyopharm: Honoraria; Roche: Consultancy, Honoraria, Research Funding; Leukemia and Lymphoma Society Canada: Research Funding; BMS: Consultancy, Honoraria; Celgene: Honoraria; Merck: Consultancy, Honoraria; Amgen: Honoraria.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,316
Score d'incertitude au seuil0,856

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,293
Écart entre enseignants0,269 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission2
Résumé présentoui

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