Maria Giovanna Scarale1, Massimiliano Copetti2, Monia Garofolo3, Andrea Fontana2, Lucia Salvemini1, Salvatore De Cosmo4, Olga Lamacchia5, Giuseppe Penno3, Vincenzo Trischitta6,7, Claudia Menzaghi6. 1. Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS "Casa Sollievo della Sofferenza," San Giovanni Rotondo, Italy. 2. Unit of Biostatistics, Fondazione IRCCS "Casa Sollievo della Sofferenza," San Giovanni Rotondo, Italy. 3. Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy. 4. Department of Clinical Sciences, Fondazione IRCCS "Casa Sollievo Della Sofferenza," San Giovanni Rotondo, Italy. 5. Unit of Endocrinology and Diabetology, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy. 6. Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS "Casa Sollievo della Sofferenza," San Giovanni Rotondo, Italy c.menzaghi@operapadrepio.it vincenzo.trischitta@uniroma1.it. 7. Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy.
Abstract
OBJECTIVE: Type 2 diabetes is characterized by increased death rate. In order to tackle this dramatic event, it becomes essential to discover novel biomarkers capable of identifying high-risk patients to be exposed to more aggressive preventive and treatment strategies. hs-CRP and serum amyloid P component (SAP) are two acute-phase inflammation proteins, which interact physically and share structural and functional features. We investigated their combined role in associating with and improving prediction of mortality in type 2 diabetes. RESEARCH DESIGN AND METHODS: Four cohorts comprising 2,499 patients with diabetes (643 all-cause deaths) were analyzed. The improvement of mortality prediction was addressed using two well-established prediction models, namely, EstimatioN oF mORtality risk in type 2 diabetiC patiEnts (ENFORCE) and Risk Equations for Complications of Type 2 Diabetes (RECODe). RESULTS: Both hs-CRP and SAP were independently associated with all-cause mortality (hazard ratios [HRs] [95% CIs]: 1.46 [1.34-1.58] [P < 0.001] and 0.82 [0.76-0.89] [P < 0.001], respectively). Patients with SAP ≤33 mg/L were at increased risk of death versus those with SAP >33 mg/L only if hs-CRP was relatively high (>2 mg/L) (HR 1.96 [95% CI 1.52-2.54] [P < 0.001] and 1.20 [0.91-1.57] [P = 0.20] in hs-CRP >2 and ≤2 mg/L subgroups, respectively; hs-CRP-by-SAP strata interaction P < 0.001). The addition of hs-CRP and SAP significantly (all P < 0.05) improved several discrimination and reclassification measures of both ENFORCE and RECODe all-cause mortality prediction models. CONCLUSIONS: In type 2 diabetes, hs-CRP and SAP show opposite and synergic associations with all-cause mortality. The use of both markers, possibly in combination with others yet to be unraveled, might improve the ability to predict the risk of death in the real-life setting.
OBJECTIVE:Type 2 diabetes is characterized by increased death rate. In order to tackle this dramatic event, it becomes essential to discover novel biomarkers capable of identifying high-risk patients to be exposed to more aggressive preventive and treatment strategies. hs-CRP and serum amyloid P component (SAP) are two acute-phase inflammation proteins, which interact physically and share structural and functional features. We investigated their combined role in associating with and improving prediction of mortality in type 2 diabetes. RESEARCH DESIGN AND METHODS: Four cohorts comprising 2,499 patients with diabetes (643 all-cause deaths) were analyzed. The improvement of mortality prediction was addressed using two well-established prediction models, namely, EstimatioN oF mORtality risk in type 2 diabetiCpatiEnts (ENFORCE) and Risk Equations for Complications of Type 2 Diabetes (RECODe). RESULTS: Both hs-CRP and SAP were independently associated with all-cause mortality (hazard ratios [HRs] [95% CIs]: 1.46 [1.34-1.58] [P < 0.001] and 0.82 [0.76-0.89] [P < 0.001], respectively). Patients with SAP ≤33 mg/L were at increased risk of death versus those with SAP >33 mg/L only if hs-CRP was relatively high (>2 mg/L) (HR 1.96 [95% CI 1.52-2.54] [P < 0.001] and 1.20 [0.91-1.57] [P = 0.20] in hs-CRP >2 and ≤2 mg/L subgroups, respectively; hs-CRP-by-SAP strata interaction P < 0.001). The addition of hs-CRP and SAP significantly (all P < 0.05) improved several discrimination and reclassification measures of both ENFORCE and RECODe all-cause mortality prediction models. CONCLUSIONS: In type 2 diabetes, hs-CRP and SAP show opposite and synergic associations with all-cause mortality. The use of both markers, possibly in combination with others yet to be unraveled, might improve the ability to predict the risk of death in the real-life setting.