BackgroundPatients with rhabdomyosarcoma (RMS) whose disease relapses have little chance of being... more BackgroundPatients with rhabdomyosarcoma (RMS) whose disease relapses have little chance of being cured, so front‐line treatments are usually followed up with surveillance imaging in an effort to detect any recurrences as early as possible, and thereby improve post‐relapse outcomes. The real benefit of such routine surveillance imaging in RMS remains to be demonstrated, however. This retrospective, single‐center study examines how well surveillance imaging identifies recurrent tumors and its impact on post‐relapse survival.MethodsThe analysis concerned 79 patients <21 years old treated between 1985 and 2020 whose initially localized RMS relapsed. Clinical findings, treatment modalities, and survival were analyzed, comparing patients whose relapse was first suspected from symptoms they developed (clinical symptoms group) with those whose relapse was identified by radiological surveillance (routine imaging group).ResultsTumor relapses came to light because of clinical symptoms in 42 cases, and on routine imaging in 37. The time to relapse was much the same in the two groups. The median overall survival (OS) and 5‐year OS rate were, respectively, 10 months and 12.6% in the clinical symptoms group, and 11 months and 27.5% in the routine imaging group (p‐value .327). Among patients with favorable prognostic scores, survival was better for those in the routine imaging group (5‐year OS 75.0% vs. 33.0%, p‐value .047).ConclusionIt remains doubtful whether surveillance imaging has any real impact on RMS relapse detection and patients’ post‐relapse survival. Further studies are needed to establish the most appropriate follow‐up recommendations, taking the potentially negative effects of regular radiological exams into account.
Background Ipilimumab (Ip) is an option in Metastatic Melanoma (MM) patients (pt) in case of dise... more Background Ipilimumab (Ip) is an option in Metastatic Melanoma (MM) patients (pt) in case of disease progression after antiPD1 (AP) treatment and BRAF+MEK inhibitors (BMi) administration (for BRAF mutated melanoma). Clinical trial are evaluating potential Ip-based combinations in 2nd/3rd line setting. Many studies underline the role of some parameters (as LDH, ECOG PS, Neutrophile/Leucocyte ratio) as progostic factors for immunotherapy used in first-line. We evaluate the prognostic role of some relevant clinical or laboratoristic parameters for Ip used in late line after AP, Bmi, in order to define pt that benefit most from Ip monotherapy in this setting. Methods A retrospective multicenter study was conducted in 8 Italian Oncology Centers, evaluating MM pt treated with Ip after AP and/or BMi. Endpoints were OS and PFS, Kaplan Mayer and Cox regression were applied for survival analysis. Results Among 200 pt that received AP or Bmi, 48 were eligible for Ip administration in 2nd/3rd line. Before Ip treatment, ECOG PS was 0 in 21 pt, number of metastatic sites was less then 3 in 14 pt, LDH was within normal range in 19 pt, NLR ratio (= baseline neutrophils/total leukocytes) was less then 0.7 in 28 pt: in univariate analysis, only ECOG PS and NLR resulted significantly associated with better PFS and OS. For pt with ECOG PS 0 or 1 medianPFS was 3.2, 2.3 month respectively (p value 0.0066; HR 0.377 IC95% 0.186-0.762), median OS was 12.1, 4.0 respectively (p value 0.0016 HR 0.287 IC95% 0.132-0.622). For pt with NLR <0,7 or > 0,7 medianPFS was 3.2, 2.0 month respectively (p value 0.002 HR 0.241 IC95% 0.0978-0.593), median OS was 7.63, 2.67 respectively (p value 0.0037 HR 0.251 IC95% 0.0986-0.0637) A score was counted for each pt considering the number of favorable basal factors present (ECOG PS 0, NLR<0.7), from 0 to 2. For pt with SCORE 0,1,2 medianPFS was 4.8, 2.4, 1.4 month respectively (p value 0.0009), median OS was 25.6, 5.8, 1.9 respectively (p value <0.0001). Conclusions ECOG PS 0, NLR <0.7, resulted prognostic factors associated with favorable PFS and OS of MM pt treated with Ip after AP or BMi progression. Subgroup with all these factors has a better prognosis. These data can help treatment choice and should be evaluated prospectively. Legal entity responsible for the study Italian Melanoma Intergroup. Funding Has not received any funding. Disclosure R. Marconcini: Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Novartis; Honoraria (self), Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: La Roche; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: MSD; Honoraria (self), Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: BMS; Honoraria (self), Advisory / Consultancy: Incyte; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Ipsen. All other authors have declared no conflicts of interest.
Summary of baseline characteristics’ distribution after the propensity score matching procedure b... more 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).
Kaplan-Meier survival estimates according to the receipt of no diabetes medication, other diabete... more Kaplan-Meier survival estimates according to the receipt of no diabetes medication, other diabetes medications/insulin therapy only, and metformin therapy (either alone or in combinations). A) Overall Survival whole cohort; patients not receiving diabetes medications: 18.9 months (95%CI: 15.9-21.6; 684 events), patients on other diabetes medications/insulin therapy only: 19.3 months (95%CI: 11.6-22.9; 48 events), patients on metformin: 12.3 months (95%CI: 9.8-15.9; 100 events). B) Progression Free Survival whole cohort; patients not receiving diabetes medications: 8.2 months (95%CI: 7.1-9.4; 872 events), patients on other diabetes medications/insulin therapy only: 10.7 months (95%CI: 6.7-11.6; 61 events), patients on metformin: 7.9 months (95%CI: 5.1-10.1; 124 events).
Summary of baseline characteristics’ distribution between patients on other oral antidiabetic dru... more Summary of baseline characteristics’ distribution between patients on other oral antidiabetic drugs/insulin only and those who were not on diabetes medications.
Kaplan-Meier survival estimates according to the receipt of other diabetes medications and insuli... more 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).
Melanoma cohort - summary of baseline characteristics’ distribution after the propensity score ma... more 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).
A) Heat map of the 770 transcripts analyzed with the Nanostring Pancancer Immune Panel in diabeti... more A) Heat map of the 770 transcripts analyzed with the Nanostring Pancancer Immune Panel in diabetic samples (n=11) compared with non-diabetic controls (n=11). B) Heat map of selected differently transcripted genes.
Purpose:No evidence exists as to whether type 2 diabetes mellitus (T2DM) impairs clinical outcome... more Purpose:No evidence exists as to whether type 2 diabetes mellitus (T2DM) impairs clinical outcome from immune checkpoint inhibitors (ICI) in patients with solid tumors.Experimental Design:In a large cohort of ICI recipients treated at 21 institutions from June 2014 to June 2020, we studied whether patients on glucose-lowering medications (GLM) for T2DM had shorter overall survival (OS) and progression-free survival (PFS). We used targeted transcriptomics in a subset of patients to explore differences in the tumor microenvironment (TME) of patients with or without diabetes.Results:A total of 1,395 patients were included. Primary tumors included non–small cell lung cancer (NSCLC; 54.7%), melanoma (24.7%), renal cell (15.0%), and other carcinomas (5.6%). After multivariable analysis, patients on GLM (n = 226, 16.2%) displayed an increased risk of death [HR, 1.29; 95% confidence interval (CI),1.07–1.56] and disease progression/death (HR, 1.21; 95% CI, 1.03–1.43) independent of number of...
Summary of baseline characteristics’ distribution after the propensity score matching procedure b... more Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on other antidiabetic drugs/insulin only and those who were not on diabetes medications (ratio 1:3, caliper 0.1).
Kaplan-Meier survival estimates according to the receipt of metformin. A) Overall Survival whole ... more 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).
Volcano plot of differentially regulated genes identified by Nanostring analysis. The Benjamini–H... more 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 <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).
NSCLC cohort - summary of baseline characteristics’ distribution after the propensity score match... more 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).
Summary of baseline characteristics’ distribution after the propensity score matching procedure b... more 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).
BackgroundPatients with rhabdomyosarcoma (RMS) whose disease relapses have little chance of being... more BackgroundPatients with rhabdomyosarcoma (RMS) whose disease relapses have little chance of being cured, so front‐line treatments are usually followed up with surveillance imaging in an effort to detect any recurrences as early as possible, and thereby improve post‐relapse outcomes. The real benefit of such routine surveillance imaging in RMS remains to be demonstrated, however. This retrospective, single‐center study examines how well surveillance imaging identifies recurrent tumors and its impact on post‐relapse survival.MethodsThe analysis concerned 79 patients &lt;21 years old treated between 1985 and 2020 whose initially localized RMS relapsed. Clinical findings, treatment modalities, and survival were analyzed, comparing patients whose relapse was first suspected from symptoms they developed (clinical symptoms group) with those whose relapse was identified by radiological surveillance (routine imaging group).ResultsTumor relapses came to light because of clinical symptoms in 42 cases, and on routine imaging in 37. The time to relapse was much the same in the two groups. The median overall survival (OS) and 5‐year OS rate were, respectively, 10 months and 12.6% in the clinical symptoms group, and 11 months and 27.5% in the routine imaging group (p‐value .327). Among patients with favorable prognostic scores, survival was better for those in the routine imaging group (5‐year OS 75.0% vs. 33.0%, p‐value .047).ConclusionIt remains doubtful whether surveillance imaging has any real impact on RMS relapse detection and patients’ post‐relapse survival. Further studies are needed to establish the most appropriate follow‐up recommendations, taking the potentially negative effects of regular radiological exams into account.
Background Ipilimumab (Ip) is an option in Metastatic Melanoma (MM) patients (pt) in case of dise... more Background Ipilimumab (Ip) is an option in Metastatic Melanoma (MM) patients (pt) in case of disease progression after antiPD1 (AP) treatment and BRAF+MEK inhibitors (BMi) administration (for BRAF mutated melanoma). Clinical trial are evaluating potential Ip-based combinations in 2nd/3rd line setting. Many studies underline the role of some parameters (as LDH, ECOG PS, Neutrophile/Leucocyte ratio) as progostic factors for immunotherapy used in first-line. We evaluate the prognostic role of some relevant clinical or laboratoristic parameters for Ip used in late line after AP, Bmi, in order to define pt that benefit most from Ip monotherapy in this setting. Methods A retrospective multicenter study was conducted in 8 Italian Oncology Centers, evaluating MM pt treated with Ip after AP and/or BMi. Endpoints were OS and PFS, Kaplan Mayer and Cox regression were applied for survival analysis. Results Among 200 pt that received AP or Bmi, 48 were eligible for Ip administration in 2nd/3rd line. Before Ip treatment, ECOG PS was 0 in 21 pt, number of metastatic sites was less then 3 in 14 pt, LDH was within normal range in 19 pt, NLR ratio (= baseline neutrophils/total leukocytes) was less then 0.7 in 28 pt: in univariate analysis, only ECOG PS and NLR resulted significantly associated with better PFS and OS. For pt with ECOG PS 0 or 1 medianPFS was 3.2, 2.3 month respectively (p value 0.0066; HR 0.377 IC95% 0.186-0.762), median OS was 12.1, 4.0 respectively (p value 0.0016 HR 0.287 IC95% 0.132-0.622). For pt with NLR &amp;amp;amp;amp;amp;amp;amp;amp;lt;0,7 or &amp;amp;amp;amp;amp;amp;amp;amp;gt; 0,7 medianPFS was 3.2, 2.0 month respectively (p value 0.002 HR 0.241 IC95% 0.0978-0.593), median OS was 7.63, 2.67 respectively (p value 0.0037 HR 0.251 IC95% 0.0986-0.0637) A score was counted for each pt considering the number of favorable basal factors present (ECOG PS 0, NLR&amp;amp;amp;amp;amp;amp;amp;amp;lt;0.7), from 0 to 2. For pt with SCORE 0,1,2 medianPFS was 4.8, 2.4, 1.4 month respectively (p value 0.0009), median OS was 25.6, 5.8, 1.9 respectively (p value &amp;amp;amp;amp;amp;amp;amp;amp;lt;0.0001). Conclusions ECOG PS 0, NLR &amp;amp;amp;amp;amp;amp;amp;amp;lt;0.7, resulted prognostic factors associated with favorable PFS and OS of MM pt treated with Ip after AP or BMi progression. Subgroup with all these factors has a better prognosis. These data can help treatment choice and should be evaluated prospectively. Legal entity responsible for the study Italian Melanoma Intergroup. Funding Has not received any funding. Disclosure R. Marconcini: Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: Novartis; Honoraria (self), Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: La Roche; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: MSD; Honoraria (self), Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: BMS; Honoraria (self), Advisory / Consultancy: Incyte; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Ipsen. All other authors have declared no conflicts of interest.
Summary of baseline characteristics’ distribution after the propensity score matching procedure b... more 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).
Kaplan-Meier survival estimates according to the receipt of no diabetes medication, other diabete... more Kaplan-Meier survival estimates according to the receipt of no diabetes medication, other diabetes medications/insulin therapy only, and metformin therapy (either alone or in combinations). A) Overall Survival whole cohort; patients not receiving diabetes medications: 18.9 months (95%CI: 15.9-21.6; 684 events), patients on other diabetes medications/insulin therapy only: 19.3 months (95%CI: 11.6-22.9; 48 events), patients on metformin: 12.3 months (95%CI: 9.8-15.9; 100 events). B) Progression Free Survival whole cohort; patients not receiving diabetes medications: 8.2 months (95%CI: 7.1-9.4; 872 events), patients on other diabetes medications/insulin therapy only: 10.7 months (95%CI: 6.7-11.6; 61 events), patients on metformin: 7.9 months (95%CI: 5.1-10.1; 124 events).
Summary of baseline characteristics’ distribution between patients on other oral antidiabetic dru... more Summary of baseline characteristics’ distribution between patients on other oral antidiabetic drugs/insulin only and those who were not on diabetes medications.
Kaplan-Meier survival estimates according to the receipt of other diabetes medications and insuli... more 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).
Melanoma cohort - summary of baseline characteristics’ distribution after the propensity score ma... more 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).
A) Heat map of the 770 transcripts analyzed with the Nanostring Pancancer Immune Panel in diabeti... more A) Heat map of the 770 transcripts analyzed with the Nanostring Pancancer Immune Panel in diabetic samples (n=11) compared with non-diabetic controls (n=11). B) Heat map of selected differently transcripted genes.
Purpose:No evidence exists as to whether type 2 diabetes mellitus (T2DM) impairs clinical outcome... more Purpose:No evidence exists as to whether type 2 diabetes mellitus (T2DM) impairs clinical outcome from immune checkpoint inhibitors (ICI) in patients with solid tumors.Experimental Design:In a large cohort of ICI recipients treated at 21 institutions from June 2014 to June 2020, we studied whether patients on glucose-lowering medications (GLM) for T2DM had shorter overall survival (OS) and progression-free survival (PFS). We used targeted transcriptomics in a subset of patients to explore differences in the tumor microenvironment (TME) of patients with or without diabetes.Results:A total of 1,395 patients were included. Primary tumors included non–small cell lung cancer (NSCLC; 54.7%), melanoma (24.7%), renal cell (15.0%), and other carcinomas (5.6%). After multivariable analysis, patients on GLM (n = 226, 16.2%) displayed an increased risk of death [HR, 1.29; 95% confidence interval (CI),1.07–1.56] and disease progression/death (HR, 1.21; 95% CI, 1.03–1.43) independent of number of...
Summary of baseline characteristics’ distribution after the propensity score matching procedure b... more Summary of baseline characteristics’ distribution after the propensity score matching procedure between patients on other antidiabetic drugs/insulin only and those who were not on diabetes medications (ratio 1:3, caliper 0.1).
Kaplan-Meier survival estimates according to the receipt of metformin. A) Overall Survival whole ... more 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).
Volcano plot of differentially regulated genes identified by Nanostring analysis. The Benjamini–H... more 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 <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).
NSCLC cohort - summary of baseline characteristics’ distribution after the propensity score match... more 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).
Summary of baseline characteristics’ distribution after the propensity score matching procedure b... more 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).
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