Tommaso Za

Dr. Tommaso Za


Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2012 in Journal of Experimental & Clinical Cancer Research
Verified
Journal Article
Open access
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FPFrancesco Pisani
Francesco Pisani
MPMaria Teresa Petrucci
Maria Teresa Petrucci
DGDiana Giannarelli
Diana Giannarelli
VBVelia Bongarzoni
Velia Bongarzoni
MMMarco Montanaro
Marco Montanaro
MPMaria Concetta Petti
Maria Concetta Petti
Immunoglobulin D multiple myeloma (MM) is rare and has a poorer prognosis than other MM isotypes.

22 January 2025 in Cancers
Verified
Journal Article
Open access
PDF file
FFFrancesca Fazio
Francesca Fazio
MGMartina Gherardini
Martina Gherardini
ERElena Rossi
Elena Rossi
TZTommaso Za
Tommaso Za
FLFrancesca Di Landro
Francesca Di Landro
MPMaria Teresa Petrucci
Maria Teresa Petrucci
Background/Objectives: Treatments for multiple myeloma (MM) have expanded in the last decade, and the overall survival (OS) of MM patients (pts) is in continuous improvement. With the availability of new treatments and the use of high-dose chemotherapy, followed by autologous hematopoietic stem cell transplantation (ASCT), the median OS of newly diagnosed MM (NDMM) pts is 6–8 years. To date, approximately 50% and 28% of MM patients are still alive at 5 years and 10 years. Few data are reported concerning the characteristics of the long-term survival MM pts. Methods: the aim of this observational multicenter study is to analyze the clinical profile of MM pts who have survived 10 years or longer, to identify possible predictors of long-term survival. Conclusions: this is a real-life observation of a cohort of 344 long-term survivors with MM. The median age of the entire cohort was 59 years (range 27–83). The median years from diagnosis was 13.4 (range 11.3–16.3). Our analysis identified age more than 60 years, hypoalbuminemia at diagnosis, and a number of anti-myeloma therapies equal or more than 3 as significant independent prognostic factors for reduced OS. These finding underline the importance of designing prospective studies to identify clinical, biological, and molecular characteristics that could be used to better stratify newly diagnosed multiple myeloma pts in order to incorporate reproducible biomarkers and to identify tailored optimal target therapies.

6 November 2025 in Cancers
Verified
Journal Article
Open access
PDF file
SMSonia Morè
Sonia Morè
Massimo OffidaniMassimo Offidani
Massimo Offidani
LCLaura Corvatta
Laura Corvatta
TZTommaso Za
Tommaso Za
FFFrancesca Fazio
Francesca Fazio
MPMaria Teresa Petrucci
Maria Teresa Petrucci
Background: Early relapse in multiple myeloma (MM) is a major predictor of poor prognosis, regardless of cytogenetic risk or treatment intensity. Methods: Here we analyzed 1026 MM patients treated across 12 Italian hematology centers. FHR was defined as progression-free survival (PFS) ≤18 months in transplant-eligible (TE) and ≤12 months in non-transplant-eligible (NTE) patients. Logistic regression and ROC analysis were used to identify significant predictors of FHR and build a risk score. Results: FHR status was identified in 175 patients (17%). These patients had significantly shorter PFS (7 vs. 57.5 months) and overall survival (19 months vs. not reached; p < 0.001). FHR status was associated with higher median LDH, lower Hb level, higher creatinine level and lower platelets count. Modified EASIX formula was built by these significant continuous variables, to be tested in a logistic analysis: [(LDH × creatinine)/(Hb × PLT) × 100]. A significantly higher rate of FHR was found with a score > 2.0 (89% vs. 11%, p < 0.001). Multivariate logistic analysis selected the above formula, ECOG PS ≥ 2 and ISS III as factors associated with FHR. Scoring these variables according to OR, three groups of patients were segregated with a rate of FHR patients of 7%, 29.5%, and 63.5%, respectively. Treatment with anti-CD38 monoclonal antibodies was associated with lower FHR frequency. Conclusions: This study proposes a simple, clinically applicable model to identify FHR MM patients early in their disease course. However, very in-depth biological tools, not available in clinical practice, are needed to identify singularly risk of becoming FHR.