NCT06447532|Enrolling By InvitationDMC
Use of Machine Learning Techniques for Serial Assessment of Systemic Inflammatory Markers in Breast Cancer Patients
INFLAMMATE
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INFLAMMATE
Sponsor study identifier
observational
4,500
8 countries
13
Study Start
August 1, 2024
Actual (reported)Primary Completion
December 31, 2024
Actual (reported)Study Completion
February 2027
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Breast cancer is the most common cancer in women globally, with 2.3 million new cases diagnosed in 2020. Hormone receptor positive (HR+), human epidermal growth factor receptor 2 negative (HER2-) breast cancer is the most prevalent subtype, comprising 69% of all breast cancers in the USA. Within the tumor immune microenvironment, a higher intensity of myeloid cell infiltration and low levels of lymphocyte infiltration have been associated with worse outcomes. Markers in peripheral blood have emerged as predictive biomarkers that can be easily obtained non-invasively and at low cost. Experiments have confirmed the relative components of these tests (such as the immune cells) directly or indirectly participated in tumour occurrence, development, and immune escape, underscoring the potential use of laboratory tests as tumour biomarkers
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
February 2027
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
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Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
April 26, 2024
Actual (reported)June 7, 2024
Actual (reported)August 1, 2024
Actual (reported)December 31, 2024
Actual (reported)February 2027
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Overall survival
Overall survival
From the date of diagnosis to the date of death, assessed up to 120 months
Disease free survival
From the date of diagnosis to the date of first progression (local recurrence of tumor or distant metastasis), assessed up to 60 months
All the participants involved in our study are women who are diagnosed breast cancer and treated with surgery or neoadjuvant chemotherapy from January 1st 2013 to December 31st 2018.
Surgery (mastectomy or quadrantectomy); Neoadjuvant chemotherapy
Registry-reported names are shown in full. Names without a link have not yet been matched to a Syfrah profile.
All the women involved in our study are patients who are diagnosed breast cancer pathologically and treated with surgery or neoadjuvant chemotherapy from January 1st 2013 to December 31st 2018.
Pablo Mandó
Buenos Aires, Buenos Aires, Argentina
Rosekeila Simoes Nomeline
Uberaba, Minas Gerais, Brazil
Tomás Reinert
Porto Alegre, Rio Grande do Sul, Brazil
Idam Oliveira Junior
Barretos, São Paulo, Brazil
César Cabello
Campinas, São Paulo, Brazil
Daniel Guimaraes Tiezzi
Ribeirão Preto, São Paulo, Brazil
Vasily Giannakeas
Toronto, Ontario, Canada
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4.
Faria SS, Giannarelli D, Cordeiro de Lima VC, Anwar SL, Casadei C, De Giorgi U, Madonna G, Ascierto PA, Mendoza Lopez RV, Chammas R, Capone M. Development of a Prognostic Model for Early Breast Cancer Integrating Neutrophil to Lymphocyte Ratio and Clinical-Pathological Characteristics. Oncologist. 2024 Apr 4;29(4):e447-e454. doi: 10.1093/oncolo/oyad303.
Afonso C Nazario, PhD
University Federal of Sao Paulo
First Submitted
April 26, 2024
First Posted
June 7, 2024
Study Start
August 1, 2024
Actual (reported)Primary Completion
December 31, 2024
Actual (reported)Adjuvant CDK4/6 Inhibitor Use in HR+/HER2- Breast Cancer
Contact the study team to confirm eligibility.
Salma Elashwah
Cairo, Egypt
Masahiro Takada
Osaka, Osaka, Japan
Masakazu Toi
Tokyo, Tokyo, 113-8677, Japan
Cynthia Mayte Villarreal Garza
Mexico City, Mexico
Wonshik Han
Seoul, South Korea
Cristina Saura
Madrid, Spain, Spain
Choi E, Bahadori MT, Schuetz A, Stewart WF, Sun J. Doctor AI: Predicting Clinical Events via Recurrent Neural Networks. JMLR Workshop Conf Proc. 2016 Aug;56:301-318. Epub 2016 Dec 10.
Study Completion
February 2027
EstimatedPlanned date reported by the registry; this milestone is not confirmed as achieved.
Last Updated
March 12, 2025
Record last verified: 2024-06
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Source: ClinicalTrials.gov.
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