Search

Your search keyword '"Bacci, S"' showing total 24 results
Start Over Author "Bacci, S" Database OAIster
24 results on '"Bacci, S"'

1. MASLD, hepatic steatosis and fibrosis are associated with the prevalence of chronic kidney disease and retinopathy in adults with type 1 diabetes mellitus

Author

Mantovani, A, Morieri, M, Aldigeri, R, Palmisano, L, Masulli, M, Bonomo, K, Baroni, M, Cossu, E, Cimini, F, Cavallo, G, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Pollis, R, Cas, A, de Kreutzenberg, S, Targher, G, Mantovani, Alessandro, Morieri, Mario Luca, Aldigeri, Raffaella, Palmisano, Luisa, Masulli, Maria, Bonomo, Katia, Baroni, Marco Giorgio, Cossu, Efisio, Cimini, Flavia Agata, Cavallo, Gisella, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Pollis, Riccardo Maria, Cas, Alessandra Dei, de Kreutzenberg, Saula Vigili, Targher, Giovanni, Mantovani, A, Morieri, M, Aldigeri, R, Palmisano, L, Masulli, M, Bonomo, K, Baroni, M, Cossu, E, Cimini, F, Cavallo, G, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Pollis, R, Cas, A, de Kreutzenberg, S, Targher, G, Mantovani, Alessandro, Morieri, Mario Luca, Aldigeri, Raffaella, Palmisano, Luisa, Masulli, Maria, Bonomo, Katia, Baroni, Marco Giorgio, Cossu, Efisio, Cimini, Flavia Agata, Cavallo, Gisella, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Pollis, Riccardo Maria, Cas, Alessandra Dei, de Kreutzenberg, Saula Vigili, and Targher, Giovanni

Abstract

Aim: We examined whether metabolic dysfunction-associated steatotic liver disease (MASLD) with or without significant fibrosis (assessed by validated non-invasive biomarkers) was associated with an increased risk of prevalent chronic kidney disease (CKD) or diabetic retinopathy in people with type 1 diabetes mellitus (T1DM). Methods: We performed a retrospective multicenter cross-sectional study involving 1,409 adult outpatients with T1DM, in whom hepatic steatosis index (HSI) and fibrosis (FIB)-4 index were calculated for non-invasively detecting hepatic steatosis (defined by HSI > 36), with or without coexisting significant fibrosis (FIB-4 index ≥ 1.3 or < 1.3). CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 or urine albumin/creatinine ratio ≥ 3.0 mg/mmol. The presence of diabetic retinopathy was also recorded in all participants. Results: Patients with MASLD and significant fibrosis (n = 93) had a remarkably higher prevalence of CKD and diabetic retinopathy than their counterparts with MASLD without fibrosis (n = 578) and those without steatosis (n = 738). After adjustment for sex, diabetes duration, hemoglobin A1c, hypertension, and use of antihypertensive or lipid-lowering medications, patients with SLD and significant fibrosis had a higher risk of prevalent CKD (adjusted-odds ratio 1.76, 95 % confidence interval 1.05–2.96) than those without steatosis. Patients with MASLD without fibrosis had a higher risk of prevalent retinopathy (adjusted-odds ratio 1.49, 95 % CI 1.13–1.46) than those without steatosis. Conclusion: This is the largest cross-sectional study showing that MASLD with and without coexisting significant fibrosis was associated, independently of potential confounders, with an increased risk of prevalent CKD and retinopathy in adults with T1DM.

Published
2024

2. Association between different modalities of insulin administration and metabolic dysfunction-associated fatty liver disease in adults with type 1 diabetes mellitus

Author

Csermely, A, Mantovani, A, Morieri, M, Palmisano, L, Masulli, M, Cossu, E, Baroni, M, Bonomo, K, Cimini, F, Cavallo, G, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Pollis, R, Aldigeri, R, Cas, A, de Kreutzenberg, S, Targher, G, Csermely, Alessandro, Mantovani, Alessandro, Morieri, Mario Luca, Palmisano, Luisa, Masulli, Maria, Cossu, Efisio, Baroni, Marco Giorgio, Bonomo, Katia, Cimini, Flavia Agata, Cavallo, Gisella, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Pollis, Riccardo Maria, Aldigeri, Raffaella, Cas, Alessandra Dei, de Kreutzenberg, Saula Vigili, Targher, Giovanni, Csermely, A, Mantovani, A, Morieri, M, Palmisano, L, Masulli, M, Cossu, E, Baroni, M, Bonomo, K, Cimini, F, Cavallo, G, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Pollis, R, Aldigeri, R, Cas, A, de Kreutzenberg, S, Targher, G, Csermely, Alessandro, Mantovani, Alessandro, Morieri, Mario Luca, Palmisano, Luisa, Masulli, Maria, Cossu, Efisio, Baroni, Marco Giorgio, Bonomo, Katia, Cimini, Flavia Agata, Cavallo, Gisella, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Pollis, Riccardo Maria, Aldigeri, Raffaella, Cas, Alessandra Dei, de Kreutzenberg, Saula Vigili, and Targher, Giovanni

Abstract

Aim: We examined whether different insulin administration modalities, i.e., multiple daily injections (MDI) or continuous subcutaneous insulin infusion (CSII by insulin pumps), are differently associated with the risk of having metabolic dysfunction-associated fatty liver disease (MAFLD), with or without coexisting significant liver fibrosis (assessed by validated non-invasive biomarkers), in adults with type 1 diabetes mellitus (T1DM). Methods: We conducted a retrospective, multicenter, cross-sectional study involving 1,417 adult individuals with established T1DM treated with MDI or CSII. We calculated hepatic steatosis index (HSI) and fibrosis (FIB)-4 index for non-invasively detecting MAFLD (defined by HSI >36), with or without coexisting significant fibrosis (defined by FIB-4 index ≥ 1.3 or <1.3, respectively). Results: Compared to the MDI group (n = 1,161), insulin-pump users (n = 256; 18.1%) were more likely to be younger (mean age: 40 vs. 48 years, P < 0.001), had better glycemic control (mean hemoglobin A1c: 7.7% vs. 7.9%, P = 0.025) and a markedly lower prevalence of MAFLD with coexisting significant fibrosis (2.7% vs. 8.1%, P = 0.010), but a comparable prevalence of MAFLD without fibrosis. In multinomial logistic regression analysis, CSII therapy was associated with a ∼70%-lower risk of MAFLD with significant fibrosis (unadjusted odds ratio 0.32, 95% confidence interval 0.14–0.70; P = 0.004), but this association was no longer significant after adjustment for age, hemoglobin A1c and other potential confounders. Conclusion: The lower prevalence of MAFLD with coexisting significant fibrosis we observed in adults with T1DM using CSII therapy, compared to those using MDI therapy, is primarily mediated by inter-group differences in age.

Published
2023

3. Hepatic steatosis with significant fibrosis is associated with an increased 10-year estimated risk of cardiovascular disease in adults with type 1 diabetes mellitus

Author

Mantovani, A, Morieri, M, Palmisano, L, Masulli, M, Cossu, E, Baroni, M, Bonomo, K, Cimini, F, Cavallo, G, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Pollis, R, Aldigeri, R, Cas, A, de Kreutzenberg, S, Targher, G, Mantovani, Alessandro, Morieri, Mario Luca, Palmisano, Luisa, Masulli, Maria, Cossu, Efisio, Baroni, Marco Giorgio, Bonomo, Katia, Cimini, Flavia Agata, Cavallo, Gisella, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Pollis, Riccardo Maria, Aldigeri, Raffaella, Cas, Alessandra Dei, de Kreutzenberg, Saula Vigili, Targher, Giovanni, Mantovani, A, Morieri, M, Palmisano, L, Masulli, M, Cossu, E, Baroni, M, Bonomo, K, Cimini, F, Cavallo, G, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Pollis, R, Aldigeri, R, Cas, A, de Kreutzenberg, S, Targher, G, Mantovani, Alessandro, Morieri, Mario Luca, Palmisano, Luisa, Masulli, Maria, Cossu, Efisio, Baroni, Marco Giorgio, Bonomo, Katia, Cimini, Flavia Agata, Cavallo, Gisella, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Pollis, Riccardo Maria, Aldigeri, Raffaella, Cas, Alessandra Dei, de Kreutzenberg, Saula Vigili, and Targher, Giovanni

Abstract

Background: We assessed whether hepatic steatosis with or without significant fibrosis (determined by validated non-invasive biomarkers) is associated with an increased 10-year estimated risk for cardiovascular disease (CVD) in people with type 1 diabetes mellitus (T1DM). Methods: We conducted a retrospective, multicenter, cross-sectional study involving 1,254 adults with established T1DM without pre-existing CVD. We used the hepatic steatosis index (HSI) and fibrosis (FIB)-4 index for non-invasively detecting hepatic steatosis (defined as HSI > 36), with or without coexisting significant fibrosis (defined as FIB-4 index ≥ 1.3 or < 1.3). We calculated the Steno type 1 risk engine and the atherosclerotic CVD (ASCVD) risk score to estimate the 10-year risk of developing a first fatal or nonfatal CVD event. Results: Using the Steno type 1 risk engine, a significantly greater proportion of patients with hepatic steatosis and significant fibrosis (n = 91) had a high 10-year estimated CVD risk compared to those with hepatic steatosis alone (n = 509) or without steatosis (n = 654) (75.8% vs. 23.2% vs. 24.9%, p < 0.001). After adjustment for sex, BMI, diabetes duration, hemoglobin A1c, chronic kidney disease, and lipid-lowering medication use, patients with hepatic steatosis and significant fibrosis had an increased 10-year estimated risk of developing a first fatal or nonfatal CVD event (adjusted-odds ratio 11.4, 95% confidence interval 3.54–36.9) than those without steatosis. We observed almost identical results using the ASCVD risk calculator. Conclusions: The 10-year estimated CVD risk is remarkably greater in T1DM adults with hepatic steatosis and significant fibrosis than in their counterparts with hepatic steatosis alone or without steatosis.

Published
2023

4. Sex differences in cardiovascular disease and cardiovascular risk estimation in patients with type 1 diabetes

Author

Dei Cas, A, Aldigeri, R, Mantovani, A, Masulli, M, Palmisano, L, Cavalot, F, Bonomo, K, Baroni, M, Cossu, E, Cavallo, G, Cimini, F, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Morieri, M, Pollis, R, Targher, G, Vigili de Kreutzenberg, S, Dei Cas, Alessandra, Aldigeri, Raffaella, Mantovani, Alessandro, Masulli, Maria, Palmisano, Luisa, Cavalot, Franco, Bonomo, Katia, Baroni, Marco Giorgio, Cossu, Efisio, Cavallo, Gisella, Cimini, Flavia Agata, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Morieri, Mario Luca, Pollis, Riccardo Maria, Targher, Giovanni, Vigili de Kreutzenberg, Saula, Dei Cas, A, Aldigeri, R, Mantovani, A, Masulli, M, Palmisano, L, Cavalot, F, Bonomo, K, Baroni, M, Cossu, E, Cavallo, G, Cimini, F, Buzzetti, R, Mignogna, C, Leonetti, F, Bacci, S, Trevisan, R, Morieri, M, Pollis, R, Targher, G, Vigili de Kreutzenberg, S, Dei Cas, Alessandra, Aldigeri, Raffaella, Mantovani, Alessandro, Masulli, Maria, Palmisano, Luisa, Cavalot, Franco, Bonomo, Katia, Baroni, Marco Giorgio, Cossu, Efisio, Cavallo, Gisella, Cimini, Flavia Agata, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Morieri, Mario Luca, Pollis, Riccardo Maria, Targher, Giovanni, and Vigili de Kreutzenberg, Saula

Abstract

Aims: Patients with type 1 diabetes (T1D) have higher cardiovascular disease (CVD) risk compared to the general population. This observational study aims to evaluate sex-related differences in CVD prevalence and CVD risk estimates in a large cohort of T1D adults. Materials and methods: We conducted a multicenter, cross-sectional study involving 2,041 T1D patients (mean age 46 years; 44.9% women). In patients without pre-existing CVD (primary prevention), we calculated the Steno type 1 risk engine to estimate the 10-year risk of developing CVD events. Results: CVD prevalence (n=116) was higher in men than in women aged ≥55 years (19.2 vs 12.8%, p=0.036), but comparable between the two sexes in those aged <55 years (p=0.91). In patients without pre-existing CVD (n=1,925), mean 10-year estimated CVD risk was 15.4±0.4% without any significant sex difference. However, stratifying this patient group by age, the 10-year estimated CVD risk was significantly higher in men than in women until age 55 years (p<0.001), but this risk equalized after this age. Carotid-artery plaque burden was significantly associated with age ≥55 years and with a medium and high 10-year estimated CVD risk, without any significant sex difference. Diabetic retinopathy and sensory-motor neuropathy were also associated with higher 10-year CVD risk and female sex. Conclusions: Both men and women with T1D are at high CVD risk. The 10-year estimated CVD risk was higher in men aged <55 years than in women of similar age, but these sex differences disappeared at age ≥55 years, suggesting that female sex was no longer protective.

Published
2023

5. Dietary intake and major food sources of polyphenols in people with type 2 diabetes: The TOSCA.IT Study

Author

Vitale, M, Masulli, M, Rivellese, A, Bonora, E, Cappellini, F, Nicolucci, A, Squatrito, S, Antenucci, D, Barrea, A, Bianchi, C, Bianchini, F, Fontana, L, Fornengo, P, Giorgino, F, Gnasso, A, Mannucci, E, Mazzotti, A, Nappo, R, Palena, A, Pata, P, Perriello, G, Potenziani, S, Radin, R, Ricci, L, Romeo, F, Santini, C, Scarponi, M, Serra, R, Timi, A, Turco, A, Vedovato, M, Zavaroni, D, Grioni, S, Riccardi, G, Vaccaro, O, Cocozza, S, Auciello, S, Cigolini, M, Pichiri, I, Brangani, C, Tomasetto, E, Sinagra, T, Longhitano, S, Tropea, V, Ballardini, G, Babini, A, Ripani, R, Gregori, G, Dolci, M, Bruselli, L, Salutini, I, Mori, M, Baccetti, F, Lapolla, A, Sartore, G, Burlina, S, Chilelli, N, Buzzetti, R, Venditti, C, Carlone, A, Galluzzo, A, Giordano, C, Torregrossa, V, Corsi, L, Cuneo, G, Corsi, S, Tizio, B, Galluzzo, G, Citro, G, Natale, M, Salvatore, V, Di Cianni, G, Lacaria, E, Russo, L, Iannarelli, R, De Gregorio, A, Sciarretta, F, D'Andrea, S, Montani, V, Cannarsa, E, Dolcetti, K, Cordera, R, Bonabello, L, Mazzucchelli, C, Giorda, C, Bonetto, C, Baldassarre, M, Iovine, C, Ciano, O, Dall'Aglio, E, Mancastroppa, G, Grimaldi, F, Tonutti, L, Boemi, M, D'Angelo, F, Leotta, S, Lauro, D, Rinaldi, M, Cignarelli, M, La Macchia, O, Fariello, S, Tomasi, F, Zamboni, C, Dozio, N, Trevisan, R, Scaranna, C, Del Prato, S, Miccoli, R, Garofolo, M, Pugliese, G, Salvi, L, Rangel, G, Anichini, R, Tedeschi, A, Corsini, E, Cucinotta, D, Di Benedetto, A, Giunta, L, Ruffo, M, Bossi, A, Carpinter, R, Dotta, F, Ceccarelli, E, Bartolo, P, Caselli, C, Luberto, A, Calbucci, G, Consoli, A, Ginestra, F, Calabrese, M, Zogheri, A, Laviola, L, Ippolito, C, Tarantino, L, Avogaro, A, Carallo, C, Scicchitano, C, Livraga, S, Perin, P, Forrnengo, P, Prinzis, T, De Cosmo, S, Bacci, S, Lamanna, C, Lettina, G, Aiello, A, Lalli, C, Franzetti, I, Petrachi, F, Asprino, V, Capra, C, Forte, E, Reggiani, G, Forlani, G, Montesi, L, Mazzella, N, Piatti, P, Monti, L, Stuccillo, M, Auletta, P, Petraroli, E, Capobianco, G, Romano, G, Cutolo, M, De Simone, G, Caiazzo, G, Nunziata, P, Sorrentino, S, Amelia, U, Calatola, P, Capuano, G, Vitale M., Masulli M., Rivellese A. A., Bonora E., Cappellini F., Nicolucci A., Squatrito S., Antenucci D., Barrea A., Bianchi C., Bianchini F., Fontana L., Fornengo P., Giorgino F., Gnasso A., Mannucci E., Mazzotti A., Nappo R., Palena A. P., Pata P., Perriello G., Potenziani S., Radin R., Ricci L., Romeo F., Santini C., Scarponi M., Serra R., Timi A., Turco A. A., Vedovato M., Zavaroni D., Grioni S., Riccardi G., Vaccaro O., Cocozza S., Auciello S., Cigolini M., Pichiri I., Brangani C., Tomasetto E., Sinagra T., Longhitano S., Tropea V., Ballardini G., Babini A. C., Ripani R., Gregori G., Dolci M., Bruselli L., Salutini I., Mori M., Baccetti F., Lapolla A., Sartore G., Burlina S., Chilelli N. C., Buzzetti R., Venditti C., Carlone A., Galluzzo A., Giordano C., Torregrossa V., Corsi L., Cuneo G., Corsi S., Tizio B., Galluzzo G., Citro G., Natale M., Salvatore V., Di Cianni G., Lacaria E., Russo L., Iannarelli R., De Gregorio A., Sciarretta F., D'Andrea S., Montani V., Cannarsa E., Dolcetti K., Cordera R., Bonabello L. A., Mazzucchelli C., Giorda C. B., Bonetto C., Baldassarre M. P. A., Iovine C., Ciano O., Dall'Aglio E., Mancastroppa G., Grimaldi F., Tonutti L., Boemi M., D'Angelo F., Leotta S., Lauro D., Rinaldi M. E., Cignarelli M., La Macchia O., Fariello S., Tomasi F., Zamboni C., Dozio N., Trevisan R., Scaranna C., Del Prato S., Miccoli R., Garofolo M., Pugliese G., Salvi L., Rangel G., Anichini R., Tedeschi A., Corsini E., Cucinotta D., Di Benedetto A., Giunta L., Ruffo M. C., Bossi A. C., Carpinter R., Dotta F., Ceccarelli E., Bartolo P. D., Caselli C., Luberto A., Calbucci G., Consoli A., Ginestra F., Calabrese M., Zogheri A., Laviola L., Ippolito C., Tarantino L., Avogaro A., Carallo C., Scicchitano C., Livraga S., Perin P. C., Forrnengo P., Prinzis T., De Cosmo S., Bacci S., Lamanna C., Lettina G., Aiello A., Lalli C., Franzetti I., Petrachi F., Asprino V., Capra C., Forte E., Reggiani G. M., Forlani G., Montesi L., Mazzella N., Piatti P. M., Monti L., Stuccillo M., Auletta P., Petraroli E., Capobianco G., Romano G., Cutolo M., De Simone G., Caiazzo G., Nunziata P., Sorrentino S., Amelia U., Calatola P., Capuano G., Vitale, M, Masulli, M, Rivellese, A, Bonora, E, Cappellini, F, Nicolucci, A, Squatrito, S, Antenucci, D, Barrea, A, Bianchi, C, Bianchini, F, Fontana, L, Fornengo, P, Giorgino, F, Gnasso, A, Mannucci, E, Mazzotti, A, Nappo, R, Palena, A, Pata, P, Perriello, G, Potenziani, S, Radin, R, Ricci, L, Romeo, F, Santini, C, Scarponi, M, Serra, R, Timi, A, Turco, A, Vedovato, M, Zavaroni, D, Grioni, S, Riccardi, G, Vaccaro, O, Cocozza, S, Auciello, S, Cigolini, M, Pichiri, I, Brangani, C, Tomasetto, E, Sinagra, T, Longhitano, S, Tropea, V, Ballardini, G, Babini, A, Ripani, R, Gregori, G, Dolci, M, Bruselli, L, Salutini, I, Mori, M, Baccetti, F, Lapolla, A, Sartore, G, Burlina, S, Chilelli, N, Buzzetti, R, Venditti, C, Carlone, A, Galluzzo, A, Giordano, C, Torregrossa, V, Corsi, L, Cuneo, G, Corsi, S, Tizio, B, Galluzzo, G, Citro, G, Natale, M, Salvatore, V, Di Cianni, G, Lacaria, E, Russo, L, Iannarelli, R, De Gregorio, A, Sciarretta, F, D'Andrea, S, Montani, V, Cannarsa, E, Dolcetti, K, Cordera, R, Bonabello, L, Mazzucchelli, C, Giorda, C, Bonetto, C, Baldassarre, M, Iovine, C, Ciano, O, Dall'Aglio, E, Mancastroppa, G, Grimaldi, F, Tonutti, L, Boemi, M, D'Angelo, F, Leotta, S, Lauro, D, Rinaldi, M, Cignarelli, M, La Macchia, O, Fariello, S, Tomasi, F, Zamboni, C, Dozio, N, Trevisan, R, Scaranna, C, Del Prato, S, Miccoli, R, Garofolo, M, Pugliese, G, Salvi, L, Rangel, G, Anichini, R, Tedeschi, A, Corsini, E, Cucinotta, D, Di Benedetto, A, Giunta, L, Ruffo, M, Bossi, A, Carpinter, R, Dotta, F, Ceccarelli, E, Bartolo, P, Caselli, C, Luberto, A, Calbucci, G, Consoli, A, Ginestra, F, Calabrese, M, Zogheri, A, Laviola, L, Ippolito, C, Tarantino, L, Avogaro, A, Carallo, C, Scicchitano, C, Livraga, S, Perin, P, Forrnengo, P, Prinzis, T, De Cosmo, S, Bacci, S, Lamanna, C, Lettina, G, Aiello, A, Lalli, C, Franzetti, I, Petrachi, F, Asprino, V, Capra, C, Forte, E, Reggiani, G, Forlani, G, Montesi, L, Mazzella, N, Piatti, P, Monti, L, Stuccillo, M, Auletta, P, Petraroli, E, Capobianco, G, Romano, G, Cutolo, M, De Simone, G, Caiazzo, G, Nunziata, P, Sorrentino, S, Amelia, U, Calatola, P, Capuano, G, Vitale M., Masulli M., Rivellese A. A., Bonora E., Cappellini F., Nicolucci A., Squatrito S., Antenucci D., Barrea A., Bianchi C., Bianchini F., Fontana L., Fornengo P., Giorgino F., Gnasso A., Mannucci E., Mazzotti A., Nappo R., Palena A. P., Pata P., Perriello G., Potenziani S., Radin R., Ricci L., Romeo F., Santini C., Scarponi M., Serra R., Timi A., Turco A. A., Vedovato M., Zavaroni D., Grioni S., Riccardi G., Vaccaro O., Cocozza S., Auciello S., Cigolini M., Pichiri I., Brangani C., Tomasetto E., Sinagra T., Longhitano S., Tropea V., Ballardini G., Babini A. C., Ripani R., Gregori G., Dolci M., Bruselli L., Salutini I., Mori M., Baccetti F., Lapolla A., Sartore G., Burlina S., Chilelli N. C., Buzzetti R., Venditti C., Carlone A., Galluzzo A., Giordano C., Torregrossa V., Corsi L., Cuneo G., Corsi S., Tizio B., Galluzzo G., Citro G., Natale M., Salvatore V., Di Cianni G., Lacaria E., Russo L., Iannarelli R., De Gregorio A., Sciarretta F., D'Andrea S., Montani V., Cannarsa E., Dolcetti K., Cordera R., Bonabello L. A., Mazzucchelli C., Giorda C. B., Bonetto C., Baldassarre M. P. A., Iovine C., Ciano O., Dall'Aglio E., Mancastroppa G., Grimaldi F., Tonutti L., Boemi M., D'Angelo F., Leotta S., Lauro D., Rinaldi M. E., Cignarelli M., La Macchia O., Fariello S., Tomasi F., Zamboni C., Dozio N., Trevisan R., Scaranna C., Del Prato S., Miccoli R., Garofolo M., Pugliese G., Salvi L., Rangel G., Anichini R., Tedeschi A., Corsini E., Cucinotta D., Di Benedetto A., Giunta L., Ruffo M. C., Bossi A. C., Carpinter R., Dotta F., Ceccarelli E., Bartolo P. D., Caselli C., Luberto A., Calbucci G., Consoli A., Ginestra F., Calabrese M., Zogheri A., Laviola L., Ippolito C., Tarantino L., Avogaro A., Carallo C., Scicchitano C., Livraga S., Perin P. C., Forrnengo P., Prinzis T., De Cosmo S., Bacci S., Lamanna C., Lettina G., Aiello A., Lalli C., Franzetti I., Petrachi F., Asprino V., Capra C., Forte E., Reggiani G. M., Forlani G., Montesi L., Mazzella N., Piatti P. M., Monti L., Stuccillo M., Auletta P., Petraroli E., Capobianco G., Romano G., Cutolo M., De Simone G., Caiazzo G., Nunziata P., Sorrentino S., Amelia U., Calatola P., and Capuano G.

Abstract

Purpose: Proper evaluation of polyphenols intake at the population level is a necessary step in order to establish possible associations with health outcomes. Available data are limited, and so far no study has been performed in people with diabetes. The aim of this work was to document the intake of polyphenols and their major food sources in a cohort of people with type 2 diabetes and in socio-demographic subgroups. Methods: We studied 2573 men and women aged 50–75 years. Among others, anthropometry was measured by standard protocol and dietary habits were investigated by food frequency questionnaire (EPIC). The intake of polyphenols was evaluated using US Department of Agriculture and Phenol-Explorer databases. Results: The mean total polyphenol intake was 683.3 ± 5.8 mg/day. Non-alcoholic beverages represented the main food source of dietary polyphenols and provided 35.5% of total polyphenol intake, followed by fruits (23.0%), alcoholic beverages (14.0%), vegetables (12.4%), cereal products and tubers (4.6%), legumes (3.7%) and oils (2.1%); chocolate, cakes and nuts are negligible sources of polyphenols in this cohort. The two most important polyphenol classes contributing to the total intake were flavonoids (47.5%) and phenolic acids (47.4%). Polyphenol intake increased with age and education level and decreased with BMI; furthermore, in the northern regions of Italy, the polyphenol intake was slightly, but significantly higher than in the central or southern regions. Conclusions: The study documents for the first time the intake of polyphenols and their main food sources in people with diabetes using validated and complete databases of the polyphenol content of food. Compared with published data, collected in people without diabetes, these results suggest a lower intake and a different pattern of intake in people with diabetes.

Published
2018

6. Multilevel Model-Based Clustering: A New Proposal of Maximum-A-Posteriori Assignment

Author

Imaizumi, T, Okada, A, Miyamoto, S, Sakaori, F, Yamamoto, Y, Vichi, M, Bacci, S, Bartolucci, F, Pennoni, F, Imaizumi, T, Okada, A, Miyamoto, S, Sakaori, F, Yamamoto, Y, Vichi, M, Bacci, S, Bartolucci, F, and Pennoni, F

Abstract

We deal with the problem of latent variable prediction in the context of multilevel latent class models for categorical responses provided by individuals nested in groups. In particular, we propose a posterior assignment rule that jointly predicts the individual- and group-level latent variables. This proposal is alternative to the common maximum- a-posteriori rule, which is based on first predicting the latent variables at cluster level and, then, those at individual level. To illustrate the proposal, we show the results of two simulation studies and two applications on data related to the national and the international assessment of student skills.

Published
2020

7. Effects on the incidence of cardiovascular events of the addition of pioglitazone versus sulfonylureas in patients with type 2 diabetes inadequately controlled with metformin (TOSCA.IT): a randomised, multicentre trial

Author

Vaccaro, O, Masulli, M, Nicolucci, A, Bonora, E, Del Prato, S, Maggioni, A, Rivellese, A, Squatrito, S, Giorda, C, Sesti, G, Mocarelli, P, Lucisano, G, Sacco, M, Signorini, S, Cappellini, F, Perriello, G, Babini, A, Lapolla, A, Gregori, G, Giordano, C, Corsi, L, Buzzetti, R, Clemente, G, Di Cianni, G, Iannarelli, R, Cordera, R, La Macchia, O, Zamboni, C, Scaranna, C, Boemi, M, Iovine, C, Lauro, D, Leotta, S, Dall'Aglio, E, Cannarsa, E, Tonutti, L, Pugliese, G, Bossi, A, Anichini, R, Dotta, F, Di Benedetto, A, Citro, G, Antenucci, D, Ricci, L, Giorgino, F, Santini, C, Gnasso, A, De Cosmo, S, Zavaroni, D, Vedovato, M, Consoli, A, Calabrese, M, di Bartolo, P, Fornengo, P, Riccardi, G, D'Angelo, F, Giansanti, R, Tanase, L, Lanari, L, Testa, I, Pancani, F, Ranchelli, A, Vagheggi, P, Scatona, A, Fontana, L, Laviola, L, Tarantino, L, Ippolito, C, Gigantelli, V, Manicone, M, Conte, E, Trevisan, R, Rota, R, Dodesini, A, Reggiani, G, Montesi, L, Mazzella, N, Forlani, G, Caselli, C, Di Luzio, R, Mazzotti, A, Aiello, A, Barrea, A, Musto, A, D'Amico, F, Sinagra, T, Longhitano, S, Trowpea, V, Sparti, M, Italia, S, Lisi, E, Grasso, G, Pezzino, V, Insalaco, F, Carallo, C, Scicchitano, C, De Franceschi, M, Calbucci, G, Ripani, R, Cuneo, G, Corsi, S, Romeo, F, Lesina, A, Comoglio, M, Bonetto, C, Robusto, A, Nada, E, Asprino, V, Cetraro, R, Impieri, M, Lucchese, G, Donnarumma, G, Tizio, B, Lenza, L, Paraggio, P, Tomasi, F, Dozio, N, Scalambra, E, Mannucci, E, Lamanna, C, Cignarelli, M, Macchia, O, Fariello, S, Sorrentino, M, Franzetti, I, Radin, R, Annunziata, F, Bonabello, L, Durante, A, Dolcino, M, Gallo, F, Mazzucchelli, C, Aleo, A, Melga, P, Briatore, L, Maggi, D, Storace, D, Cecoli, F, D'Ugo, E, Pupillo, M, Baldassarre, M, Salvati, F, Minnucci, A, De Luca, A, Zugaro, A, Santarelli, L, Bosco, A, Petrella, V, La Verghetta, G, D'Andrea, S, Giuliani, A, Polidoro, W, Sperandio, A, Sciarretta, F, Pezzella, A, Carlone, A, Potenziani, S, Venditti, C, Foffi, C, Carbone, S, Cipolloni, L, Moretti, C, Leto, G, Serra, R, Petrachi, F, Romano, I, Lacaria, E, Russo, L, Goretti, C, Sannino, C, Dolci, M, Bruselli, L, Mori, M, Baccetti, F, Del Freo, M, Cucinotta, D, Giunta, L, Ruffo, M, Cannizzaro, D, Pintaudi, B, Perrone, G, Pata, P, Ragonese, F, Lettina, G, Mancuso, T, Coppolino, A, Piatti, P, Monti, L, Stuccillo, M, Lucotti, P, Setola, M, Crippa, G, Loi, C, Oldani, M, Bottalico, M, Pellegata, B, Bonomo, M, Menicatti, L, Resi, V, Bertuzzi, F, Disoteo, E, Pizzi, G, Annuzzi, G, Capaldo, B, Nappo, R, Auciello, S, Turco, A, Costagliola, L, Corte, G, Vallefuoco, P, Nappi, F, Vitale, M, Cocozza, S, Ciano, O, Massimino, E, Garofalo, N, Avogaro, A, Guarneri, G, Fedele, D, Sartore, G, Chilelli, N, Burlina, S, Bonsembiante, B, Galluzzo, A, Torregrossa, V, Mancastroppa, G, Arsenio, L, Cioni, F, Caronna, S, Papi, M, Santeusanio, F, Calagreti, G, Timi, A, Tantucci, A, Marino, C, Ginestra, F, Di Biagio, R, Taraborelli, M, Miccoli, R, Bianchi, C, Garofolo, M, Politi, K, Penno, G, Livraga, S, Calzoni, F, Corsini, E, Tedeschi, A, Gagliano, M, Ippolito, G, Salutini, E, Cervellino, F, Natale, M, Salvatore, V, Zampino, A, Sinisi, R, Arcangeli, A, Zogheri, A, Guizzotti, S, Longo, R, Pellicano, F, Scolozzi, P, Termine, S, Luberto, A, Ballardini, G, Trojani, C, Mazzuca, P, Bruglia, M, Ciamei, M, Genghini, S, Zannoni, C, Rangel, G, Salvi, L, Zappaterreno, A, Cordone, S, Simonelli, P, Meggiorini, M, Frasheri, A, Di Pippo, C, Maglio, C, Mazzitelli, G, Rinaldi, M, Galli, A, Romano, M, D'Angelo, P, Suraci, C, Bacci, S, Palena, A, Genovese, S, Mancino, M, Rondinelli, M, Capone, F, Calabretto, E, Bulgheroni, M, Bucciarelli, L, Ceccarelli, E, Fondelli, C, Santacroce, C, Guarino, E, Nigi, L, Lalli, C, Di Vizia, G, Scarponi, M, Montani, V, Di Bernardino, P, Romagni, P, Dolcetti, K, Forte, E, Tamburo, L, Perin, P, Prinzis, T, Gruden, G, Bruno, G, Zucco, C, Perotta, M, Marena, S, Monsignore, S, Panero, F, Ponzi, F, Carpinteri, R, Casagrande, M, Coletti, M, Balini, A, Filopanti, M, Madaschi, S, Pulcina, A, Grimaldi, F, Venturini, G, Agus, S, Pagnutti, S, Guidotti, F, Cavarape, A, Cigolini, M, Pichiri, I, Brangani, C, Fainelli, G, Tomasetto, E, Zoppini, G, Galletti, A, Perrone, D, Capra, C, Bianchini, F, Ceseri, M, Di Nardo, B, Sasso, E, Bartolomei, B, Suliman, I, Fabbri, G, Romano, G, Maturo, N, Nunziata, G, Capobianco, G, De Simone, G, Villa, V, Rota, G, Pentangelo, C, Carbonara, O, Caiazzo, G, Cutolo, M, Sorrentino, T, Mastrilli, V, Amelia, U, Masi, S, Corigliano, G, Gaeta, I, Armentano, V, Calatola, P, Capuano, G, Angiulli, B, Auletta, P, Petraroli, E, Iodice, C, Agrusta, M, Vaccaro O., Masulli M., Nicolucci A., Bonora E., Del Prato S., Maggioni A. P., Rivellese A. A., Squatrito S., Giorda C. B., Sesti G., Mocarelli P., Lucisano G., Sacco M., Signorini S., Cappellini F., Perriello G., Babini A. C., Lapolla A., Gregori G., Giordano C., Corsi L., Buzzetti R., Clemente G., Di Cianni G., Iannarelli R., Cordera R., La Macchia O., Zamboni C., Scaranna C., Boemi M., Iovine C., Lauro D., Leotta S., Dall'Aglio E., Cannarsa E., Tonutti L., Pugliese G., Bossi A. C., Anichini R., Dotta F., Di Benedetto A., Citro G., Antenucci D., Ricci L., Giorgino F., Santini C., Gnasso A., De Cosmo S., Zavaroni D., Vedovato M., Consoli A., Calabrese M., di Bartolo P., Fornengo P., Riccardi G., D'Angelo F., Giansanti R., Tanase L., Lanari L., Testa I., Pancani F., Ranchelli A., Vagheggi P., Scatona A., Fontana L., Laviola L., Tarantino L., Ippolito C., Gigantelli V., Manicone M., Conte E., Trevisan R., Rota R., Dodesini A. R., Reggiani G. M., Montesi L., Mazzella N., Forlani G., Caselli C., Di Luzio R., Mazzotti A., Aiello A., Barrea A., Musto A., D'Amico F., Sinagra T., Longhitano S., Trowpea V., Sparti M., Italia S., Lisi E., Grasso G., Pezzino V., Insalaco F., Carallo C., Scicchitano C., De Franceschi M. S., Calbucci G., Ripani R., Cuneo G., Corsi S., Romeo F., Lesina A., Comoglio M., Bonetto C., Robusto A., Nada E., Asprino V., Cetraro R., Impieri M., Lucchese G., Donnarumma G., Tizio B., Lenza L., Paraggio P., Tomasi F., Dozio N., Scalambra E., Mannucci E., Lamanna C., Cignarelli M., Macchia O. L., Fariello S., Sorrentino M. R., Franzetti I., Radin R., Annunziata F., Bonabello L. A., Durante A., Dolcino M., Gallo F., Mazzucchelli C., Aleo A., Melga P., Briatore L., Maggi D., Storace D., Cecoli F., D'Ugo E., Pupillo M., Baldassarre M. P. A., Salvati F., Minnucci A., De Luca A., Zugaro A., Santarelli L., Bosco A., Petrella V., La Verghetta G. G., D'Andrea S., Giuliani A. E., Polidoro W. L., Sperandio A., Sciarretta F., Pezzella A., Carlone A., Potenziani S., Venditti C., Foffi C., Carbone S., Cipolloni L., Moretti C., Leto G., Serra R., Petrachi F., Romano I., Lacaria E., Russo L., Goretti C., Sannino C., Dolci M., Bruselli L., Mori M. L., Baccetti F., Del Freo M., Cucinotta D., Giunta L., Ruffo M. C., Cannizzaro D., Pintaudi B., Perrone G., Pata P., Ragonese F., Lettina G., Mancuso T., Coppolino A., Piatti P. M., Monti L., Stuccillo M., Lucotti P., Setola M., Crippa G. V., Loi C., Oldani M., Bottalico M. L., Pellegata B., Bonomo M., Menicatti L. S. M., Resi V., Bertuzzi F., Disoteo E. O., Pizzi G., Annuzzi G., Capaldo B., Nappo R., Auciello S. M., Turco A. A., Costagliola L., Corte G. D., Vallefuoco P., Nappi F., Vitale M., Cocozza S., Ciano O., Massimino E., Garofalo N., Avogaro A., Guarneri G., Fedele D., Sartore G., Chilelli N. C., Burlina S., Bonsembiante B., Galluzzo A., Torregrossa V., Mancastroppa G., Arsenio L., Cioni F., Caronna S., Papi M., Santeusanio F., Calagreti G., Timi A., Tantucci A., Marino C., Ginestra F., Di Biagio R., Taraborelli M., Miccoli R., Bianchi C., Garofolo M., Politi K. S., Penno G., Livraga S., Calzoni F., Mancastroppa G. L. F., Corsini E., Tedeschi A., Gagliano M. S., Ippolito G., Salutini E., Cervellino F., Natale M., Salvatore V., Zampino A., Sinisi R., Arcangeli A., Zogheri A., Guizzotti S., Longo R., Pellicano F., Scolozzi P., Termine S., Luberto A., Ballardini G., Trojani C., Mazzuca P., Bruglia M., Ciamei M., Genghini S., Zannoni C., Rangel G., Salvi L., Zappaterreno A., Cordone S., Simonelli P., Meggiorini M., Frasheri A., Di Pippo C., Maglio C., Mazzitelli G., Rinaldi M. E., Galli A., Romano M., D'Angelo P., Suraci C., Bacci S., Palena A. P., Genovese S., Mancino M., Rondinelli M., Capone F., Calabretto E., Bulgheroni M., Bucciarelli L., Ceccarelli E., Fondelli C., Santacroce C., Guarino E., Nigi L., Lalli C., Di Vizia G., Scarponi M., Montani V., Di Bernardino P., Romagni P., Dolcetti K., Forte E., Tamburo L., Perin P. C., Prinzis T., Gruden G., Bruno G., Zucco C., Perotta M., Marena S., Monsignore S., Panero F., Ponzi F., Carpinteri R., Casagrande M. L., Coletti M. F., Balini A., Filopanti M., Madaschi S., Pulcina A., Grimaldi F., Venturini G., Agus S., Pagnutti S., Guidotti F., Cavarape A., Cigolini M., Pichiri I., Brangani C., Fainelli G., Tomasetto E., Zoppini G., Galletti A., Perrone D., Capra C., Bianchini F., Ceseri M., Di Nardo B., Sasso E., Bartolomei B., Suliman I., Fabbri G., Romano G., Maturo N., Nunziata G., Capobianco G., De Simone G., Villa V., Rota G., Pentangelo C., Carbonara O., Caiazzo G., Cutolo M., Sorrentino T., Mastrilli V., Amelia U., Masi S., Corigliano G., Gaeta I., Armentano V., Calatola P., Capuano G., Angiulli B., Auletta P., Petraroli E., Iodice C. E., Agrusta M., Vaccaro, O, Masulli, M, Nicolucci, A, Bonora, E, Del Prato, S, Maggioni, A, Rivellese, A, Squatrito, S, Giorda, C, Sesti, G, Mocarelli, P, Lucisano, G, Sacco, M, Signorini, S, Cappellini, F, Perriello, G, Babini, A, Lapolla, A, Gregori, G, Giordano, C, Corsi, L, Buzzetti, R, Clemente, G, Di Cianni, G, Iannarelli, R, Cordera, R, La Macchia, O, Zamboni, C, Scaranna, C, Boemi, M, Iovine, C, Lauro, D, Leotta, S, Dall'Aglio, E, Cannarsa, E, Tonutti, L, Pugliese, G, Bossi, A, Anichini, R, Dotta, F, Di Benedetto, A, Citro, G, Antenucci, D, Ricci, L, Giorgino, F, Santini, C, Gnasso, A, De Cosmo, S, Zavaroni, D, Vedovato, M, Consoli, A, Calabrese, M, di Bartolo, P, Fornengo, P, Riccardi, G, D'Angelo, F, Giansanti, R, Tanase, L, Lanari, L, Testa, I, Pancani, F, Ranchelli, A, Vagheggi, P, Scatona, A, Fontana, L, Laviola, L, Tarantino, L, Ippolito, C, Gigantelli, V, Manicone, M, Conte, E, Trevisan, R, Rota, R, Dodesini, A, Reggiani, G, Montesi, L, Mazzella, N, Forlani, G, Caselli, C, Di Luzio, R, Mazzotti, A, Aiello, A, Barrea, A, Musto, A, D'Amico, F, Sinagra, T, Longhitano, S, Trowpea, V, Sparti, M, Italia, S, Lisi, E, Grasso, G, Pezzino, V, Insalaco, F, Carallo, C, Scicchitano, C, De Franceschi, M, Calbucci, G, Ripani, R, Cuneo, G, Corsi, S, Romeo, F, Lesina, A, Comoglio, M, Bonetto, C, Robusto, A, Nada, E, Asprino, V, Cetraro, R, Impieri, M, Lucchese, G, Donnarumma, G, Tizio, B, Lenza, L, Paraggio, P, Tomasi, F, Dozio, N, Scalambra, E, Mannucci, E, Lamanna, C, Cignarelli, M, Macchia, O, Fariello, S, Sorrentino, M, Franzetti, I, Radin, R, Annunziata, F, Bonabello, L, Durante, A, Dolcino, M, Gallo, F, Mazzucchelli, C, Aleo, A, Melga, P, Briatore, L, Maggi, D, Storace, D, Cecoli, F, D'Ugo, E, Pupillo, M, Baldassarre, M, Salvati, F, Minnucci, A, De Luca, A, Zugaro, A, Santarelli, L, Bosco, A, Petrella, V, La Verghetta, G, D'Andrea, S, Giuliani, A, Polidoro, W, Sperandio, A, Sciarretta, F, Pezzella, A, Carlone, A, Potenziani, S, Venditti, C, Foffi, C, Carbone, S, Cipolloni, L, Moretti, C, Leto, G, Serra, R, Petrachi, F, Romano, I, Lacaria, E, Russo, L, Goretti, C, Sannino, C, Dolci, M, Bruselli, L, Mori, M, Baccetti, F, Del Freo, M, Cucinotta, D, Giunta, L, Ruffo, M, Cannizzaro, D, Pintaudi, B, Perrone, G, Pata, P, Ragonese, F, Lettina, G, Mancuso, T, Coppolino, A, Piatti, P, Monti, L, Stuccillo, M, Lucotti, P, Setola, M, Crippa, G, Loi, C, Oldani, M, Bottalico, M, Pellegata, B, Bonomo, M, Menicatti, L, Resi, V, Bertuzzi, F, Disoteo, E, Pizzi, G, Annuzzi, G, Capaldo, B, Nappo, R, Auciello, S, Turco, A, Costagliola, L, Corte, G, Vallefuoco, P, Nappi, F, Vitale, M, Cocozza, S, Ciano, O, Massimino, E, Garofalo, N, Avogaro, A, Guarneri, G, Fedele, D, Sartore, G, Chilelli, N, Burlina, S, Bonsembiante, B, Galluzzo, A, Torregrossa, V, Mancastroppa, G, Arsenio, L, Cioni, F, Caronna, S, Papi, M, Santeusanio, F, Calagreti, G, Timi, A, Tantucci, A, Marino, C, Ginestra, F, Di Biagio, R, Taraborelli, M, Miccoli, R, Bianchi, C, Garofolo, M, Politi, K, Penno, G, Livraga, S, Calzoni, F, Corsini, E, Tedeschi, A, Gagliano, M, Ippolito, G, Salutini, E, Cervellino, F, Natale, M, Salvatore, V, Zampino, A, Sinisi, R, Arcangeli, A, Zogheri, A, Guizzotti, S, Longo, R, Pellicano, F, Scolozzi, P, Termine, S, Luberto, A, Ballardini, G, Trojani, C, Mazzuca, P, Bruglia, M, Ciamei, M, Genghini, S, Zannoni, C, Rangel, G, Salvi, L, Zappaterreno, A, Cordone, S, Simonelli, P, Meggiorini, M, Frasheri, A, Di Pippo, C, Maglio, C, Mazzitelli, G, Rinaldi, M, Galli, A, Romano, M, D'Angelo, P, Suraci, C, Bacci, S, Palena, A, Genovese, S, Mancino, M, Rondinelli, M, Capone, F, Calabretto, E, Bulgheroni, M, Bucciarelli, L, Ceccarelli, E, Fondelli, C, Santacroce, C, Guarino, E, Nigi, L, Lalli, C, Di Vizia, G, Scarponi, M, Montani, V, Di Bernardino, P, Romagni, P, Dolcetti, K, Forte, E, Tamburo, L, Perin, P, Prinzis, T, Gruden, G, Bruno, G, Zucco, C, Perotta, M, Marena, S, Monsignore, S, Panero, F, Ponzi, F, Carpinteri, R, Casagrande, M, Coletti, M, Balini, A, Filopanti, M, Madaschi, S, Pulcina, A, Grimaldi, F, Venturini, G, Agus, S, Pagnutti, S, Guidotti, F, Cavarape, A, Cigolini, M, Pichiri, I, Brangani, C, Fainelli, G, Tomasetto, E, Zoppini, G, Galletti, A, Perrone, D, Capra, C, Bianchini, F, Ceseri, M, Di Nardo, B, Sasso, E, Bartolomei, B, Suliman, I, Fabbri, G, Romano, G, Maturo, N, Nunziata, G, Capobianco, G, De Simone, G, Villa, V, Rota, G, Pentangelo, C, Carbonara, O, Caiazzo, G, Cutolo, M, Sorrentino, T, Mastrilli, V, Amelia, U, Masi, S, Corigliano, G, Gaeta, I, Armentano, V, Calatola, P, Capuano, G, Angiulli, B, Auletta, P, Petraroli, E, Iodice, C, Agrusta, M, Vaccaro O., Masulli M., Nicolucci A., Bonora E., Del Prato S., Maggioni A. P., Rivellese A. A., Squatrito S., Giorda C. B., Sesti G., Mocarelli P., Lucisano G., Sacco M., Signorini S., Cappellini F., Perriello G., Babini A. C., Lapolla A., Gregori G., Giordano C., Corsi L., Buzzetti R., Clemente G., Di Cianni G., Iannarelli R., Cordera R., La Macchia O., Zamboni C., Scaranna C., Boemi M., Iovine C., Lauro D., Leotta S., Dall'Aglio E., Cannarsa E., Tonutti L., Pugliese G., Bossi A. C., Anichini R., Dotta F., Di Benedetto A., Citro G., Antenucci D., Ricci L., Giorgino F., Santini C., Gnasso A., De Cosmo S., Zavaroni D., Vedovato M., Consoli A., Calabrese M., di Bartolo P., Fornengo P., Riccardi G., D'Angelo F., Giansanti R., Tanase L., Lanari L., Testa I., Pancani F., Ranchelli A., Vagheggi P., Scatona A., Fontana L., Laviola L., Tarantino L., Ippolito C., Gigantelli V., Manicone M., Conte E., Trevisan R., Rota R., Dodesini A. R., Reggiani G. M., Montesi L., Mazzella N., Forlani G., Caselli C., Di Luzio R., Mazzotti A., Aiello A., Barrea A., Musto A., D'Amico F., Sinagra T., Longhitano S., Trowpea V., Sparti M., Italia S., Lisi E., Grasso G., Pezzino V., Insalaco F., Carallo C., Scicchitano C., De Franceschi M. S., Calbucci G., Ripani R., Cuneo G., Corsi S., Romeo F., Lesina A., Comoglio M., Bonetto C., Robusto A., Nada E., Asprino V., Cetraro R., Impieri M., Lucchese G., Donnarumma G., Tizio B., Lenza L., Paraggio P., Tomasi F., Dozio N., Scalambra E., Mannucci E., Lamanna C., Cignarelli M., Macchia O. L., Fariello S., Sorrentino M. R., Franzetti I., Radin R., Annunziata F., Bonabello L. A., Durante A., Dolcino M., Gallo F., Mazzucchelli C., Aleo A., Melga P., Briatore L., Maggi D., Storace D., Cecoli F., D'Ugo E., Pupillo M., Baldassarre M. P. A., Salvati F., Minnucci A., De Luca A., Zugaro A., Santarelli L., Bosco A., Petrella V., La Verghetta G. G., D'Andrea S., Giuliani A. E., Polidoro W. L., Sperandio A., Sciarretta F., Pezzella A., Carlone A., Potenziani S., Venditti C., Foffi C., Carbone S., Cipolloni L., Moretti C., Leto G., Serra R., Petrachi F., Romano I., Lacaria E., Russo L., Goretti C., Sannino C., Dolci M., Bruselli L., Mori M. L., Baccetti F., Del Freo M., Cucinotta D., Giunta L., Ruffo M. C., Cannizzaro D., Pintaudi B., Perrone G., Pata P., Ragonese F., Lettina G., Mancuso T., Coppolino A., Piatti P. M., Monti L., Stuccillo M., Lucotti P., Setola M., Crippa G. V., Loi C., Oldani M., Bottalico M. L., Pellegata B., Bonomo M., Menicatti L. S. M., Resi V., Bertuzzi F., Disoteo E. O., Pizzi G., Annuzzi G., Capaldo B., Nappo R., Auciello S. M., Turco A. A., Costagliola L., Corte G. D., Vallefuoco P., Nappi F., Vitale M., Cocozza S., Ciano O., Massimino E., Garofalo N., Avogaro A., Guarneri G., Fedele D., Sartore G., Chilelli N. C., Burlina S., Bonsembiante B., Galluzzo A., Torregrossa V., Mancastroppa G., Arsenio L., Cioni F., Caronna S., Papi M., Santeusanio F., Calagreti G., Timi A., Tantucci A., Marino C., Ginestra F., Di Biagio R., Taraborelli M., Miccoli R., Bianchi C., Garofolo M., Politi K. S., Penno G., Livraga S., Calzoni F., Mancastroppa G. L. F., Corsini E., Tedeschi A., Gagliano M. S., Ippolito G., Salutini E., Cervellino F., Natale M., Salvatore V., Zampino A., Sinisi R., Arcangeli A., Zogheri A., Guizzotti S., Longo R., Pellicano F., Scolozzi P., Termine S., Luberto A., Ballardini G., Trojani C., Mazzuca P., Bruglia M., Ciamei M., Genghini S., Zannoni C., Rangel G., Salvi L., Zappaterreno A., Cordone S., Simonelli P., Meggiorini M., Frasheri A., Di Pippo C., Maglio C., Mazzitelli G., Rinaldi M. E., Galli A., Romano M., D'Angelo P., Suraci C., Bacci S., Palena A. P., Genovese S., Mancino M., Rondinelli M., Capone F., Calabretto E., Bulgheroni M., Bucciarelli L., Ceccarelli E., Fondelli C., Santacroce C., Guarino E., Nigi L., Lalli C., Di Vizia G., Scarponi M., Montani V., Di Bernardino P., Romagni P., Dolcetti K., Forte E., Tamburo L., Perin P. C., Prinzis T., Gruden G., Bruno G., Zucco C., Perotta M., Marena S., Monsignore S., Panero F., Ponzi F., Carpinteri R., Casagrande M. L., Coletti M. F., Balini A., Filopanti M., Madaschi S., Pulcina A., Grimaldi F., Venturini G., Agus S., Pagnutti S., Guidotti F., Cavarape A., Cigolini M., Pichiri I., Brangani C., Fainelli G., Tomasetto E., Zoppini G., Galletti A., Perrone D., Capra C., Bianchini F., Ceseri M., Di Nardo B., Sasso E., Bartolomei B., Suliman I., Fabbri G., Romano G., Maturo N., Nunziata G., Capobianco G., De Simone G., Villa V., Rota G., Pentangelo C., Carbonara O., Caiazzo G., Cutolo M., Sorrentino T., Mastrilli V., Amelia U., Masi S., Corigliano G., Gaeta I., Armentano V., Calatola P., Capuano G., Angiulli B., Auletta P., Petraroli E., Iodice C. E., and Agrusta M.

Abstract

Background The best treatment option for patients with type 2 diabetes in whom treatment with metformin alone fails to achieve adequate glycaemic control is debated. We aimed to compare the long-term effects of pioglitazone versus sulfonylureas, given in addition to metformin, on cardiovascular events in patients with type 2 diabetes. Methods TOSCA.IT was a multicentre, randomised, pragmatic clinical trial, in which patients aged 50–75 years with type 2 diabetes inadequately controlled with metformin monotherapy (2–3 g per day) were recruited from 57 diabetes clinics in Italy. Patients were randomly assigned (1:1), by permuted blocks randomisation (block size 10), stratified by site and previous cardiovascular events, to add-on pioglitazone (15–45 mg) or a sulfonylurea (5–15 mg glibenclamide, 2–6 mg glimepiride, or 30–120 mg gliclazide, in accordance with local practice). The trial was unblinded, but event adjudicators were unaware of treatment assignment. The primary outcome, assessed with a Cox proportional-hazards model, was a composite of first occurrence of all-cause death, non-fatal myocardial infarction, non-fatal stroke, or urgent coronary revascularisation, assessed in the modified intention-to-treat population (all randomly assigned participants with baseline data available and without any protocol violations in relation to inclusion or exclusion criteria). This study is registered with ClinicalTrials.gov, number NCT00700856. Findings Between Sept 18, 2008, and Jan 15, 2014, 3028 patients were randomly assigned and included in the analyses. 1535 were assigned to pioglitazone and 1493 to sulfonylureas (glibenclamide 24 [2%], glimepiride 723 [48%], gliclazide 745 [50%]). At baseline, 335 (11%) participants had a previous cardiovascular event. The study was stopped early on the basis of a futility analysis after a median follow-up of 57·3 months. The primary outcome occurred in 105 patients (1·5 per 100 person-years) who were given pioglitazone and 108 (1·5 p

Published
2017

9. Optimal model-based clustering with multilevel data

Author

Yoshiro Yamamoto, Takafumi Kubota, Koji Kurihara, Masahiro Mizuta, Miki Nakai, Junji Nakano, Atsuho Nakayama, Makiko Oda, Takuya Ohmori, Kosuke Okusa, Fumitake Sakaori, Kumiko Shiina, Akinobu Takeuchi, Makoto Tomita, Yuki Toyoda, Hiroshi Yadohisa, Satoru Yokoyama, Bacci, S, Bartolucci, F, Pennoni, F, PENNONI, FULVIA, Yoshiro Yamamoto, Takafumi Kubota, Koji Kurihara, Masahiro Mizuta, Miki Nakai, Junji Nakano, Atsuho Nakayama, Makiko Oda, Takuya Ohmori, Kosuke Okusa, Fumitake Sakaori, Kumiko Shiina, Akinobu Takeuchi, Makoto Tomita, Yuki Toyoda, Hiroshi Yadohisa, Satoru Yokoyama, Bacci, S, Bartolucci, F, Pennoni, F, and PENNONI, FULVIA

Abstract

In many contexts, sample units are clustered in groups according to a certain criterion, for instance employees in firms, students in classes, or patients in hospitals. These data are analyzed by multilevel models (Goldstein, 2011) and have important applications in the evaluation of public services, particularly in education and health. For instance, it may be of interest to make comparisons between schools or classes at national and international level on the basis of the students’acquired knowledge. Accountability systems in education have been promoted in the statistical literature mainly since the 90’s by Goldstein and Spiegelhalter (1996), who supported the idea that the performance monitoring approach may improve efficiency. In this work, we focus on models in which the multilevel structure is accounted for by a hierarchical set of discrete latent variables, even in the presence of multivariate responses; these latent variables are used to represent the unobserved heterogeneity between clusters (i.e., groups) of units and between units in each cluster, extending the Latent Class (LC) approach (Lazarsfeld and Henry, 1968) to the multilevel setting. In particular, two cases are of interest. The first is when the observed outcomes are polytomous, as they correspond to item responses, and data are collected at the same time occasion. This approach has been applied by many authors in the educational context, see among others Vermunt (2008) and Gnaldi et al. (2016). The second case of interest is when the data have a longitudinal dimension and heterogeneity between units is represented in a dynamic fashion by a Latent Markov (LM) chain, as proposed in Bartolucci et al. (2011); see also Bartolucci et al. (2013). While maximum likelihood estimation through the Expectation-Maximization algorithm (Dempster et al. 1977) of the models mentioned above is already well established, an issue that still deserves attention is that of predicting the latent variables at cluster

Published
2017

13. Optimal model-based clustering with multilevel data

Author

Yoshiro Yamamoto, Takafumi Kubota, Koji Kurihara, Masahiro Mizuta, Miki Nakai, Junji Nakano, Atsuho Nakayama, Makiko Oda, Takuya Ohmori, Kosuke Okusa, Fumitake Sakaori, Kumiko Shiina, Akinobu Takeuchi, Makoto Tomita, Yuki Toyoda, Hiroshi Yadohisa, Satoru Yokoyama, Bacci, S, Bartolucci, F, Pennoni, F, PENNONI, FULVIA, Yoshiro Yamamoto, Takafumi Kubota, Koji Kurihara, Masahiro Mizuta, Miki Nakai, Junji Nakano, Atsuho Nakayama, Makiko Oda, Takuya Ohmori, Kosuke Okusa, Fumitake Sakaori, Kumiko Shiina, Akinobu Takeuchi, Makoto Tomita, Yuki Toyoda, Hiroshi Yadohisa, Satoru Yokoyama, Bacci, S, Bartolucci, F, Pennoni, F, and PENNONI, FULVIA

Abstract

In many contexts, sample units are clustered in groups according to a certain criterion, for instance employees in firms, students in classes, or patients in hospitals. These data are analyzed by multilevel models (Goldstein, 2011) and have important applications in the evaluation of public services, particularly in education and health. For instance, it may be of interest to make comparisons between schools or classes at national and international level on the basis of the students’acquired knowledge. Accountability systems in education have been promoted in the statistical literature mainly since the 90’s by Goldstein and Spiegelhalter (1996), who supported the idea that the performance monitoring approach may improve efficiency. In this work, we focus on models in which the multilevel structure is accounted for by a hierarchical set of discrete latent variables, even in the presence of multivariate responses; these latent variables are used to represent the unobserved heterogeneity between clusters (i.e., groups) of units and between units in each cluster, extending the Latent Class (LC) approach (Lazarsfeld and Henry, 1968) to the multilevel setting. In particular, two cases are of interest. The first is when the observed outcomes are polytomous, as they correspond to item responses, and data are collected at the same time occasion. This approach has been applied by many authors in the educational context, see among others Vermunt (2008) and Gnaldi et al. (2016). The second case of interest is when the data have a longitudinal dimension and heterogeneity between units is represented in a dynamic fashion by a Latent Markov (LM) chain, as proposed in Bartolucci et al. (2011); see also Bartolucci et al. (2013). While maximum likelihood estimation through the Expectation-Maximization algorithm (Dempster et al. 1977) of the models mentioned above is already well established, an issue that still deserves attention is that of predicting the latent variables at cluster

Published
2017

14. A PC-1 amino acid variant (K121Q) is associated with faster progression of renal disease in patients with type 1 diabetes and albuminuria

Author

De Cosmo, S, Argiolas, A, Miscio, G, Thomas, S, Piras, G, Trevisan, R, Perin, P, Bacci, S, Zucaro, L, Margaglione, M, Frittitta, L, Pizzuti, A, Tassi, V, Viberti, G, Trischitta, V, De Cosmo S, Argiolas A, Miscio G, Thomas S, Piras GP, Trevisan R, Perin PC, Bacci S, Zucaro L, Margaglione M, Frittitta L, Pizzuti A, Tassi V, Viberti GC, Trischitta V, De Cosmo, S, Argiolas, A, Miscio, G, Thomas, S, Piras, G, Trevisan, R, Perin, P, Bacci, S, Zucaro, L, Margaglione, M, Frittitta, L, Pizzuti, A, Tassi, V, Viberti, G, Trischitta, V, De Cosmo S, Argiolas A, Miscio G, Thomas S, Piras GP, Trevisan R, Perin PC, Bacci S, Zucaro L, Margaglione M, Frittitta L, Pizzuti A, Tassi V, Viberti GC, and Trischitta V

Abstract

Insulin resistance characterizes type I diabetes in patients with albuminuria. A PC-1 glycoprotein amino acid variant, K121Q, is associated with insulin resistance. We examined the impact of the PC-1 K121Q variant on the rate of decline of the glomerular filtration rate (GFR) by creatinine clearance derived from the Cockroft-Gault formula in 77 type I diabetic patients with albuminuria who were followed for an average of 6.5 years (range 2.5-15). Patients carrying the Q allele (n = 22; 20 with KQ and 2 with QQ genotypes) had a faster GFR decline than those patients with the KK genotype (n = 55) (median 7.2 vs. 3.7 ml · min-1 · year-1; range 0.16 to 16.6 vs. -3.8 to 16.0 ml · min-1 · year-1; P< 0.001). Significantly more patients carrying the Q allele belonged to the highest tertile of GFR decline (odds ratio = 5.7, 95% CI 4.1-7.2, P = 0.02). Levels of blood pressure, HbA(1c), and albuminuria were comparable in the two genotype groups. Albuminuria (P = 0.001), mean blood pressure (P = 0.046), and PC-1 genotype (P = 0.036) independently correlated with GFR decline. Because all patients were receiving antihypertensive treatment, the faster GFR decline in the patients carrying the Q allele could be the result of reduced sensitivity to the renoprotective effect of antihypertensive therapy. PC-1 genotyping identifies type I diabetic patients with a faster progression of diabetic nephropathy.

Published
2000

15. Longitudinal analysis of self-reported health status by mixture latent auto-regressive models

Author

Bartolucci, F, Bacci, S, Pennoni, F, PENNONI, FULVIA, Bartolucci, F, Bacci, S, Pennoni, F, and PENNONI, FULVIA

Abstract

Motivated by an application to a longitudinal data set coming from the Health and Retirement Study about self-reported health status, we propose a model for longitudinal data which is based on a latent process to account for the unobserved heterogeneity between sample units in a dynamic fashion. The latent process is modelled by a mixture of auto-regressive AR(1) processes with different means and correlation coefficients, but with equal variances. We show how to perform maximum likelihood estimation of the proposed model by the joint use of an expectation–maximization algorithm and a Newton–Raphson algorithm, implemented by means of recursions developed in the hidden Markov model literature. We also introduce a simple method to obtain standard errors for the parameter estimates and suggest a strategy to choose the number of mixture components. In the application the response variable is ordinal; however, the approach may also be applied in other settings. Moreover, the application to the self-reported health status data set allows us to show that the model proposed is more flexible than other models for longitudinal data based on a continuous latent process. The model also achieves a goodness of fit that is similar to that of models based on a discrete latent process following a Markov chain, while retaining a reduced number of parameters. The effect of different formulations of the latent structure of the model is evaluated in terms of estimates of the regression parameters for the covariates.

Published
2014

16. A comparison of some criteria for states selection in the latent Markov model for longitudinal data

Author

Bacci, S, Pandolfi, S, Pennoni, F, PENNONI, FULVIA, Bacci, S, Pandolfi, S, Pennoni, F, and PENNONI, FULVIA

Abstract

We compare different selection criteria to choose the number of latent states of a multivariate latent Markov model for longitudinal data. This model is based on an underlying Markov chain to represent the evolution of a latent characteristic of a group of individuals over time. Then, the response variables observed at different occasions are assumed to be conditionally independent given this chain. Maximum likelihood estimation of the model is carried out through an Expectation-Maximization algorithm based on forward-backward recursions which are well known in the hidden Markov literature for time series. The selection criteria we consider are based on penalized versions of the maximum log-likelihood or on the posterior probabilities of belonging to each latent state, that is, the conditional probability of the latent state given the observed data. Among the latter criteria, we propose an appropriate entropy measure tailored for the latent Markov models. We show the results of a Monte Carlo simulation study aimed at comparing the performance of the above states selection criteria on the basis of a wide set of model specifications. © 2013 Springer-Verlag Berlin Heidelberg.

Published
2014

18. Markov-switching autoregressive latent variable models for longitudinal data

Author

Bacci, S, Bartolucci, F, Pennoni, F, PENNONI, FULVIA, Bacci, S, Bartolucci, F, Pennoni, F, and PENNONI, FULVIA

Abstract

We propose a generalization of the autoregressive latent variable models for longitudinal database on an AR(1) process to represent the effect of unobservable factors on the response variables. The generalization is based on correlation coefficient depending on the regime of the chain. Some particular cases are discussed in detail and illustrated by an application to a longitudinal dataset about self-evaluetion of the health status.

Published
2010

19. Markov-switching autoregressive latent variable models for longitudinal data

Author

Bacci, S, Bartolucci, F, Pennoni, F, PENNONI, FULVIA, Bacci, S, Bartolucci, F, Pennoni, F, and PENNONI, FULVIA

Abstract

We propose a generalization of the autoregressive latent variable models for longitudinal database on an AR(1) process to represent the effect of unobservable factors on the response variables. The generalization is based on correlation coefficient depending on the regime of the chain. Some particular cases are discussed in detail and illustrated by an application to a longitudinal dataset about self-evaluetion of the health status.

Published
2010

20. Tacrolimus causes reduced GLI1 expression and phenotypic changes in the TE 354.T basal cell carcinoma cell line

Author

Di Gennaro, P, Sestini, R, Bacci, S, Pacini, Andrea, Pinzani, P, Domenici, L, Toscano, A, Massi, D, Carli, P, Genuardi, Maurizio, Romagnoli, P, Pacini, A, Genuardi, M (ORCID:0000-0002-7410-8351), Di Gennaro, P, Sestini, R, Bacci, S, Pacini, Andrea, Pinzani, P, Domenici, L, Toscano, A, Massi, D, Carli, P, Genuardi, Maurizio, Romagnoli, P, Pacini, A, and Genuardi, M (ORCID:0000-0002-7410-8351)

Abstract

NO ABSTRACT

Published
2009

21. Outbreak of Clostridium difficile 027 in North Zealand, Denmark, 2008-2009

Author

Bacci, S, St-Martin, G, Olesen, B, Bruun, B, Olsen, K E P, Nielsen, E Møller, Mølbak, K, Bacci, S, St-Martin, G, Olesen, B, Bruun, B, Olsen, K E P, Nielsen, E Møller, and Mølbak, K

Abstract

Udgivelsesdato: 2009-Apr, We report an outbreak of Clostridium difficile PCR ribotype 027 in Denmark. The outbreak includes to date 73 cases from the area north of Copenhagen, but there may be related cases elsewhere in Zealand. Most infections are healthcare-associated and in patients who previously received antibiotic treatment. The strain is resistant to moxifloxacin, erythromycin, and clindamycin, and carries genes for toxin A, toxin B, and for the binary toxin. The antimicrobial pattern differs from that of the strain involved in a small cluster in Denmark in 2006-2007. Because of this outbreak, hygienic measures in the involved hospitals have been reinforced. Nationwide, microbiological laboratories were alerted to the outbreak and encouraged to send isolates for toxin profiling and PCR ribotyping.

Published
2009

22. Outbreak of Clostridium difficile 027 in North Zealand, Denmark, 2008-2009

Author

Bacci, S, St-Martin, G, Olesen, B, Bruun, B, Olsen, K E P, Nielsen, E Møller, Mølbak, K, Bacci, S, St-Martin, G, Olesen, B, Bruun, B, Olsen, K E P, Nielsen, E Møller, and Mølbak, K

Abstract

Udgivelsesdato: 2009-Apr, We report an outbreak of Clostridium difficile PCR ribotype 027 in Denmark. The outbreak includes to date 73 cases from the area north of Copenhagen, but there may be related cases elsewhere in Zealand. Most infections are healthcare-associated and in patients who previously received antibiotic treatment. The strain is resistant to moxifloxacin, erythromycin, and clindamycin, and carries genes for toxin A, toxin B, and for the binary toxin. The antimicrobial pattern differs from that of the strain involved in a small cluster in Denmark in 2006-2007. Because of this outbreak, hygienic measures in the involved hospitals have been reinforced. Nationwide, microbiological laboratories were alerted to the outbreak and encouraged to send isolates for toxin profiling and PCR ribotyping.

Published
2009

23. Retrospective survival analysis and cost-effectiveness evaluation of second allogeneic bone marrow transplantation in patients with acute leukemia. Gruppo Italiano Trapianto di Midollo Osseo

Author

Messori, A, Bosi, A, Bacci, S, Laszlo, D, Trippoli, S, Locatelli, Franco, Van Lint, M T, Di Bartolomeo, P, Amici, A, Locatelli, F (ORCID:0000-0002-7976-3654), Messori, A, Bosi, A, Bacci, S, Laszlo, D, Trippoli, S, Locatelli, Franco, Van Lint, M T, Di Bartolomeo, P, Amici, A, and Locatelli, F (ORCID:0000-0002-7976-3654)

Abstract

The therapeutic options for patients with acute leukemia who relapse after the initial transplant include second bone marrow transplantation (2BMT) and conventional chemotherapy (CC), In this work, we conducted an analysis of published survival data and we evaluated the cost-effectiveness of 2BMT in comparison with CC. We retrieved survival information on 167 patients treated with 2BMT and 299 patients treated with CC. Survival figures were derived from individual patient data and were compared between 2BMT and CC. The mean lifetime survival (MLS) was estimated for each of the two patient cohorts using standard techniques of survival-curve extrapolation, The cost data of patients given 2BMT or CC were estimated from published data. Our analysis of individual survival data showed that 2BMT improved survival at levels of statistical significance (survival gain = 19.6 months per patient). Using an incremental cost of $90 000 per patient, the cost-effectiveness ratio of 2BMT in comparison with CC was calculated as $52 215 discounted dollars per discounted life year gained. Our results indicate that, in patients with acute leukemia who relapse after their first transplant, 2BMT significantly prolongs survival in comparison with CC and seems to have an acceptable cost-effectiveness profile.

Published
1999

24. Second allogeneic bone marrow transplantation in acute leukemia: a multicenter study from the Gruppo Italiano Trapianto Di Midollo Osseo (GITMO)

Author

Bosi, A, Bacci, S, Miniero, R, Locatelli, Franco, Laszlo, D, Longo, G, Busca, A, Van Lint, M T, Di Bartolomeo, P, Amici, A, Locatelli, F (ORCID:0000-0002-7976-3654), Bosi, A, Bacci, S, Miniero, R, Locatelli, Franco, Laszlo, D, Longo, G, Busca, A, Van Lint, M T, Di Bartolomeo, P, Amici, A, and Locatelli, F (ORCID:0000-0002-7976-3654)

Abstract

Thirty-eight second allogeneic bone marrow transplants (BMT) for acute leukemia relapsed after first BMT were performed in 13 Italian centers between 1987 and 1994. Twenty-one patients had acute myelogenous leukemia (AML), 17 acute lymphoblastic leukemia (ALL); at second BMT 24 patients were in complete remission (CR) and 14 in relapse. The median time to relapse after first BMT was 10 months (range 1-70). Grade II or greater acute graft-versus-host disease (GVHD) after second transplant occurred in 34.2% of patients and a chronic GVHD in 31.5% of patients. Twenty-four patients died: seven from early transplant-related mortality (IRM), 13 from relapse and four from late toxicity. As of 31 July 1996, at a median follow-up of 47 months (range 22-85), there are 14 survivors. The three-year probability of TRM, relapse and event-free survival (EFS) is 28%, 40% and 42% respectively. In 20 of 27 evaluable patients, remission duration after second BMT was longer than after the first BMT. A diagnosis of AML was correlated with a better outcome. These data support the usefulness of second allograft in selected patients with AML relapsing after a first BMT.

Published
1997

Catalog

Books, media, physical & digital resources
See catalog results