Imperial College London

Dr. David James PINATO

Faculty of MedicineDepartment of Surgery & Cancer

Clinical Reader in Medical Oncology
 
 
 
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Contact

 

+44 (0)20 7594 2799david.pinato Website

 
 
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Location

 

ICTEM buildingHammersmith Campus

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Summary

 

Publications

Publication Type
Year
to

445 results found

Vithayathil M, D'Alessio A, Fulgenzi CAM, Nishida N, Schönlein M, von Felden J, Schulze K, Wege H, Saeed A, Wietharn B, Hildebrand H, Wu L, Ang C, Marron TU, Weinmann A, Galle PR, Bettinger D, Bengsch B, Vogel A, Balcar L, Scheiner B, Lee P-C, Huang Y-H, Amara S, Muzaffar M, Naqash AR, Cammarota A, Zanuso V, Pressiani T, Pinter M, Cortellini A, Kudo M, Rimassa L, Pinato DJ, Sharma Ret al., 2023, Impact of body mass index in patients receiving atezolizumab plus bevacizumab for hepatocellular carcinoma., Hepatol Int, Vol: 17, Pages: 904-914

BACKGROUND: Atezolizumab plus bevacizumab (Atezo/Bev) is first line-treatment for unresectable hepatocellular carcinoma (HCC). Body mass index (BMI) has demonstrated predictive value for response to immunotherapy in non-HCC cancer types. Our study investigated the effect of BMI on safety and efficacy of real-life use of Atezo/Bev for unresectable HCC. METHODS: 191 consecutive patients from seven centres receiving Atezo/Bev were included in the retrospective study. Overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and disease control rate (DCR) defined by RECIST v1.1 were measured in overweight (BMI ≥ 25) and non-overweight (BMI < 25) patients. Treatment-related adverse events (trAEs) were evaluated. RESULTS: Patients in the overweight cohort (n = 94) had higher rates of non-alcoholic fatty liver disease (NAFLD) and lower rates of Hepatitis B compared to non-overweight cohort (n = 97). Baseline Child-Pugh class and Barcelona Clinic Liver Cancer stage were similar between cohorts, with lower rates of extrahepatic spread in the overweight group. Overweight patients had similar OS compared to non-overweight (median OS 15.1 vs. 14.9 months; p = 0.99). BMI did not influence median PFS (7.1 vs. 6.1 months; p = 0.42), ORR (27.2% vs. 22.0%; p = 0.44) and DCR (74.1% vs. 71.9%; p = 0.46). There were higher rates of atezolizumab-related fatigue (22.3% vs. 10.3%; p = 0.02) and bevacizumab-related thrombosis (8.5% vs. 2.1%; p = 0.045) in the overweight patients, but overall trAEs and treatment discontinuation were comparable between cohorts. CONCLUSION: Atezo/Bev has comparable efficacy in overweight HCC patients, with an increase in treatment-related fatigue and thrombosis. Combination therapy is safe and efficacious to use in overweight patients, including those with underlying NAFLD.

Journal article

Pinter M, Scheiner B, Pinato DJ, 2023, Immune checkpoint inhibitors in hepatocellular carcinoma: emerging challenges in clinical practice., Lancet Gastroenterol Hepatol, Vol: 8, Pages: 760-770

Systemic therapy for advanced hepatocellular carcinoma has expanded at an unprecedented pace over the past 5 years. After tyrosine kinase inhibitors dominated the field for more than a decade, immune checkpoint inhibitor (ICI)-based therapies have become the main component in systemic first-line treatment of this cancer. Delivery of immunotherapy in routine clinical practice recognises several challenges. In this Viewpoint, we discuss the major gaps in knowledge around the role of ICI-based therapies in patients with Child-Pugh class B. We discuss the challenges in individuals with rare histological subtypes of primary liver cancer, including combined hepatocellular-cholangiocarcinoma, fibrolamellar hepatocellular carcinoma, and sarcomatoid hepatocellular carcinoma. We also review data on ICI rechallenge in patients previously treated with ICIs, and discuss atypical patterns of progression related to immunotherapy (ie, hyperprogressive disease and pseudoprogression).

Journal article

Pinato DJ, D'Alessio A, Celsa C, Manfredi GF, Fulgenzi CAMet al., 2023, The price and value of therapeutic synergy in liver cancer., Lancet

Journal article

El Zarif T, Nassar AH, Adib E, Fitzgerald BG, Huang J, Mouhieddine TH, Rubinstein PG, Nonato T, McKay RR, Li M, Mittra A, Owen DH, Baiocchi RA, Lorentsen M, Dittus C, Dizman N, Falohun A, Abdel-Wahab N, Diab A, Bankapur A, Reed A, Kim C, Arora A, Shah NJ, El-Am E, Kozaily E, Abdallah W, Al-Hader A, Abu Ghazal B, Saeed A, Drolen C, Lechner MG, Drakaki A, Baena J, Nebhan CA, Haykal T, Morse MA, Cortellini A, Pinato DJ, Dalla Pria A, Hall E, Bakalov V, Bahary N, Rajkumar A, Mangla A, Shah V, Singh P, Aboubakar Nana F, Lopetegui-Lia N, Dima D, Dobbs RW, Funchain P, Saleem R, Woodford R, Long GV, Menzies AM, Genova C, Barletta G, Puri S, Florou V, Idossa D, Saponara M, Queirolo P, Lamberti G, Addeo A, Bersanelli M, Freeman D, Xie W, Reid EG, Chiao EY, Sharon E, Johnson DB, Ramaswami R, Bower M, Emu B, Marron TU, Choueiri TK, Baden LR, Lurain K, Sonpavde GP, Naqash ARet al., 2023, Safety and Activity of Immune Checkpoint Inhibitors in People Living With HIV and Cancer: A Real-World Report From the Cancer Therapy Using Checkpoint Inhibitors in People Living With HIV-International (CATCH-IT) Consortium., J Clin Oncol, Vol: 41, Pages: 3712-3723

PURPOSE: Compared with people living without HIV (PWOH), people living with HIV (PWH) and cancer have traditionally been excluded from immune checkpoint inhibitor (ICI) trials. Furthermore, there is a paucity of real-world data on the use of ICIs in PWH and cancer. METHODS: This retrospective study included PWH treated with anti-PD-1- or anti-PD-L1-based therapies for advanced cancers. Kaplan-Meier method was used to estimate overall survival (OS) and progression-free survival (PFS). Objective response rates (ORRs) were measured per RECIST 1.1 or other tumor-specific criteria, whenever feasible. Restricted mean survival time (RMST) was used to compare OS and PFS between matched PWH and PWOH with metastatic NSCLC (mNSCLC). RESULTS: Among 390 PWH, median age was 58 years, 85% (n = 331) were males, 36% (n = 138) were Black; 70% (n = 274) received anti-PD-1/anti-PD-L1 monotherapy. Most common cancers were NSCLC (28%, n = 111), hepatocellular carcinoma ([HCC]; 11%, n = 44), and head and neck squamous cell carcinoma (HNSCC; 10%, n = 39). Seventy percent (152/216) had CD4+ T cell counts ≥200 cells/µL, and 94% (179/190) had HIV viral load <400 copies/mL. Twenty percent (79/390) had any grade immune-related adverse events (irAEs) and 7.7% (30/390) had grade ≥3 irAEs. ORRs were 69% (nonmelanoma skin cancer), 31% (NSCLC), 16% (HCC), and 11% (HNSCC). In the matched mNSCLC cohort (61 PWH v 110 PWOH), 20% (12/61) PWH and 22% (24/110) PWOH had irAEs. Adjusted 42-month RMST difference was -0.06 months (95% CI, -5.49 to 5.37; P = .98) for PFS and 2.23 months (95% CI, -4.02 to 8.48; P = .48) for OS. CONCLUSION: Among PWH, ICIs demonstrated differential activity across cancer types with no excess toxicity. Safety and activity of ICIs were similar between matched cohorts of PWH and PWOH with mNSCLC.

Journal article

Aboagye E, Lu H, Lou H, Wengert G, Paudel R, Patel N, Desai S, Crum W, Linton-Reid K, Chen M, Li D, Ip J, Mauri F, Pinato DJ, Rockall A, Copley SJ, Ghaem-Maghami Set al., 2023, Tumour and local lymphoid tissue interaction determines prognosis in high grade serous ovarian cancer, Cell Reports Medicine, Vol: 4, Pages: 1-24, ISSN: 2666-3791

Tertiary lymphoid structure (TLS) is associated with prognosis in copy number-driven tumours,including high grade serous ovarian cancer (HGSOC), although the function of TLS and its interactionwith copy-number alterations in HGSOC is not fully understood. In the current study, we confirmthat TLS-high HGSOC patients show significantly better progression free survival. We show thatpresence of TLS in HGSOC tumours is associated with B-cell maturation and cytotoxic tumourspecific T-cells activation and proliferation. Additionally, the copy number loss of IL15 and CXCL10may limit TLS formation in HGSOC; a list of genes that may dysregulate TLS function is also proposed.Manuscript Click here to view linked ReferencesLastly, a radiomics-based signature is developed to predict presence of TLS, which independentlypredicts PFS in both HGSOC patients and ICI-treated NSCLC patients. Overall, we reveal that TLScoordinates intratumoural B-cell and T-cell response against HGSOC tumour, while cancer genomeevolves to counteract TLS formation and function.

Journal article

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Figure S8 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Volcano plot of differentially regulated genes identified by Nanostring analysis. The Benjamini–Hockberg P-values are correlated to fold-changes in transcripts identified in diabetic samples (n = 11) versus non-diabetic controls (n = 11). The transcripts achieving the highest statistical significance (p value &lt;0.05) are highlighted by the presence of the corresponding gene name. Significantly downregulated transcripts: HRAS, Ras oncogene family (p=0.009); GTF3C1, transcription factor of the TFIIIC complex (p=0.018); LAG3, key immune checkpoint for T cell modulation (p=0.023); BIRC5, survivin – modulator of programmed cell death (p=0.038); CXCL9 (p=0.038) and CXCL11 (p=0.048), two chemokines mediating inflammatory response; OAS3, interferon-induced enzyme (p=0.04). Significantly upregulated transcripts: IL22RA1, cytokine receptor (p=0.01); MME, transmembrane glycoprotein (p=0.02).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Figure S6 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Scatter diagram with regression line summarizing the linear regression analysis between the median baseline glycaemia (used as independent variable: x-axes) and median baseline NLR (used as dependent variable: y-axes). 133 patients included; A significant regression equation was found F(1,131)= 4.09, p = 0.04) with an R2 of .030. NLR: neutrophil to lymphocyte ratio.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Figure S4 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Kaplan-Meier survival estimates according to the receipt of other diabetes medications and insulin therapy. A) Overall Survival whole cohort; patients on other oral antidiabetic drugs and insulin therapy: 17.5 months (95%CI: 12.8-20.9; 82 events), patients not receiving other oral diabetes medications and insulin therapy 17.8 months (95%CI: 15.4 – 19.7; 750 events). B) Progression Free Survival whole cohort; other oral diabetes medications and insulin therapy: 8.2 months (95%CI: 6.2-11.4; 106 events), patients not receiving other oral diabetes medications and insulin therapy: 8.1 months (95%CI: 7.1 – 9.2; 951 events).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Figure S1 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Kaplan-Meier survival estimates according to the receipt of any diabetes medication. A) Overall Survival NSCLC matched cohort; patients on any diabetes medication: 14.2 months (95%CI: 9.0 – 17.5; 99 events), patients not receiving diabetes medications: 17.5 months (95%CI: 14.2 – 26.6; 77 events). B) Progression Free Survival NSCLC matched cohort; patients on any diabetes medication: 7.9 months (95%CI: 5.4 – 10.8; 113 events), patients not receiving diabetes medications: 10.1 months (95%CI: 7.7 – 13.8; 99 events). C) Overall Survival Melanoma matched cohort; patients on any diabetes medication: 22.9 months (95%CI: 12.0 – NR; 25 events), patients not receiving diabetes medications: NR months (95%CI: 28.8 – NR; 52 events). D) Progression Free Survival Melanoma matched cohort; patients on any diabetes medication: 11.4 months (95%CI: 4.9 – 23.4; 37 events), patients not receiving diabetes medications: 13.8 months (95%CI: 8.7 – 26.0; 77 events). NR: not reached; PSM: propensity score matching.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Figure S3 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Kaplan-Meier survival estimates according to the receipt of metformin. A) Overall Survival whole cohort; patients on metformin: 12.4 months (95%CI: 10.5-16.3; 100 events), patients not receiving metformin: 19.0 months (95%CI: 16.4 – 21.1; 732 events). B) Progression Free Survival whole cohort; patients on metformin: 7.9 months (95%CI: 5.3-10.1; 124 events), patients not receiving metformin: 8.3 months (95%CI: 7.3 – 9.5; 933 events).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S11 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics of patients included in the targeted transcriptome analysis.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S8 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution between patients on other oral antidiabetic drugs/insulin only and those who were not on diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S8 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution between patients on other oral antidiabetic drugs/insulin only and those who were not on diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S4 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;NSCLC cohort - summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:1, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S5 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Melanoma cohort - summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S6 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution between patients on metformin only and those who were not on diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S7 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on metformin only and patients who were not receiving diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S4 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;NSCLC cohort - summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:1, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S3 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:2, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Methods S1 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Tumour micron-environment transcriptome analysis.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S10 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Detailed random blood sugar test results used to compute the median baseline glycaemia (MBG). 133 patients included (30 from the Pascale Cancer Institute and 103 from Imperial College London Cohort.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S2 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Details of diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S7 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on metformin only and patients who were not receiving diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S10 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Detailed random blood sugar test results used to compute the median baseline glycaemia (MBG). 133 patients included (30 from the Pascale Cancer Institute and 103 from Imperial College London Cohort.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S6 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution between patients on metformin only and those who were not on diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S5 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Melanoma cohort - summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:3, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S1 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Participating centres’ list.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S2 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Details of diabetes medications.&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S3 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on diabetes medications and those who were not receiving diabetes medications (ratio 1:2, caliper 0.1).&lt;/p&gt;</jats:p>

Other

Cortellini A, D'Alessio A, Cleary S, Buti S, Bersanelli M, Bordi P, Tonini G, Vincenzi B, Tucci M, Russo A, Pantano F, Russano M, Stucci LS, Sergi MC, Falconi M, Zarzana MA, Santini D, Spagnolo F, Tanda ET, Rastelli F, Giorgi FC, Pergolesi F, Giusti R, Filetti M, Lo Bianco F, Marchetti P, Botticelli A, Gelibter A, Siringo M, Ferrari M, Marconcini R, Vitale MG, Nicolardi L, Chiari R, Ghidini M, Nigro O, Grossi F, De Tursi M, Di Marino P, Queirolo P, Bracarda S, Macrini S, Inno A, Zoratto F, Veltri E, Spoto C, Vitale MG, Cannita K, Gennari A, Morganstein DL, Mallardo D, Nibid L, Sabarese G, Brunetti L, Perrone G, Ascierto PA, Ficorella C, Pinato DJet al., 2023, Supplementary Table S11 from Type 2 Diabetes Mellitus and Efficacy Outcomes from Immune Checkpoint Blockade in Patients with Cancer

<jats:p>&lt;p&gt;Summary of baseline characteristics of patients included in the targeted transcriptome analysis.&lt;/p&gt;</jats:p>

Other

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