Results 211 to 220 of about 280,195 (357)

A Phase I Trial of Evorpacept, Lenalidomide, and Rituximab for Patients with B-Cell Non-Hodgkin Lymphoma. [PDF]

Clin Cancer Res
Strati P, Feng L, Tyshevich A, Shavronskaya D, Alesse J, English N, Sheehan E, Syzrantsev N, Nesmelov A, Zhuang TZ, Chihara D, Westin JR, Ahmed S, Fayad LE, Henderson J, Dent K, McChesney E, Neelapu SS, Flowers CR.   +18 more
europepmc   +1 more source

Effect of blueberry extract on enhancement of radiosensitivity in non-Hodgkin lymphoma by modulating proliferation and apoptosis. [PDF]

Daru
Moradloo N, Arab S, Jam HR, Asgharzadeh S, Shokri S, Nasehi L, Nokhodchi A.   +6 more
europepmc   +1 more source

Circulating CD44 and intercellular adhesion molecule‐1 levels in low grade non‐Hodgkin lymphoma and B‐cell chronic lymphocytic leukemia patients during interferon‐α‐2a treatment [PDF]

, 2000
Meral Beksaç, Mutlu Arat, Hamdi Akan, Haluk Koç, Osman İlhan, Muhıt Özcan   +5 more
openalex   +1 more source

B-cell non-Hodgkin lymphoma linked to Coxiella burnetii.

Blood, 2016
C. Melenotte, M. Million, G. Audoly, A. Gorse, H. Dutronc, Gauthier Roland, M. Dekel, A. Moreno, S. Cammilleri, M. Carrieri, C. Protopopescu, P. Ruminy, H. Lepidi, B. Nadel, J. Mege, L. Xerri, D. Raoult   +16 more
semanticscholar   +1 more source

Artificial intelligence for risk assessment and outcome prediction in malignant haematology

British Journal of Haematology, EarlyView.
Machine learning models allow for dynamic and scalable risk stratification and outcome prediction. Different modalities of data such as electronic health records, patient genetics or laboratory results can be used as input. ML models autonomously select features weighing their prognostic value. Methods of model explainability in feature selection allow
Jan‐Niklas Eckardt, Wencke Walter, Jan Moritz Middeke, Torsten Haferlach   +3 more
wiley   +1 more source

Transformation of Classical Hodgkin Lymphoma Into Non-Hodgkin Lymphoma: Three Case Reports From the West Bank. [PDF]

Case Rep Oncol Med
Abboushi MB, Marouf O, AbuBaha M, Salameh H, Soradi R, Amer RA.   +5 more
europepmc   +1 more source

Non‐Hodgkin lymphoma subtype distribution, geodemographic patterns, and survival in the US: A longitudinal analysis of the National Cancer Data Base from 1998 to 2011

American journal of hematology/oncology, 2015
Mohammed Al-Hamadani, T. Habermann, J. Cerhan, W. Macon, M. Maurer, R. Go   +5 more
semanticscholar   +1 more source

Evaluation and forecasting methods to estimate number of patients with non-Hodgkin lymphoma: a systematic literature review. [PDF]

Popul Health Metr
Lin D, Shao C, Rogers JR, Burcu M, Sineshaw HM.   +4 more
europepmc   +1 more source

Transformed follicular non-Hodgkin lymphoma.

Blood, 2015
C. Casulo, W. R. Burack, J. Friedberg, J. Wilmot, Cancer Center   +4 more
semanticscholar   +1 more source

The impact of Foxp3+ regulatory T‐cells on CD8+ T‐cell dysfunction in tumour microenvironments and responses to immune checkpoint inhibitors

British Journal of Pharmacology, EarlyView.
Immune checkpoint inhibitors (ICIs) have been a breakthrough in cancer therapy, inducing durable remissions in responding patients. However, they are associated with variable outcomes, spanning from disease hyperprogression to complete responses with the onset of immune‐related adverse events.
Mikhaël Attias, Ciriaco A. Piccirillo
wiley   +1 more source