Machine Learning versus Cox Models for Predicting Overall Survival in Patients with Osteosarcoma: A Retrospective Analysis of the EURAMOS-1 Clinical Trial Data.

Since the mid-1980s, there has been little progress in improving survival of patients diagnosed with osteosarcoma. Survival prediction models play a key role in clinical decision-making, guiding healthcare professionals in tailoring treatment strategies based on individual patient risks. The increasing interest of the medical community in using machine learning (ML) for predicting survival has sparked an ongoing debate on the value of ML techniques versus more traditional statistical modelling (SM) approaches. This study investigates the use of SM versus ML methods in predicting overall survival (OS) using osteosarcoma data from the EURAMOS-1 clinical trial (NCT00134030). The well-established Cox proportional hazard model is compared to the extended Cox model that includes time-varying effects, and to the ML methods random survival forests and survival neural networks. The impact of eight variables on OS predictions is explored. Results are compared on different model performance metrics, variable importance, and patient-specific predictions. The article provides comprehensive insights to aid healthcare researchers in evaluating diverse survival prediction models for low-dimensional clinical data.

Survival after resection of malignant peripheral nerve sheath tumors: Introducing and validating a novel type-specific prognostic model.

Background: This study aimed to assess the performance of currently available risk calculators in a cohort of patients with malignant peripheral nerve sheath tumors (MPNST) and to create an MPNST-specific prognostic model including type-specific predictors for overall survival (OS). Methods: This is a retrospective multicenter cohort study of patients with MPNST from 11 secondary or tertiary centers in The Netherlands, Italy and the United States of America. All patients diagnosed with primary MPNST who underwent macroscopically complete surgical resection from 2000 to 2019 were included in this study. A multivariable Cox proportional hazard model for OS was estimated with prespecified predictors (age, grade, size, NF-1 status, triton status, depth, tumor location, and surgical margin). Model performance was assessed for the Sarculator and PERSARC calculators by examining discrimination (C-index) and calibration (calibration plots and observed-expected statistic; O/E-statistic). Internal-external cross-validation by different regions was performed to evaluate the generalizability of the model. Results: A total of 507 patients with primary MPNSTs were included from 11 centers in 7 regions. During follow-up (median 8.7 years), 211 patients died. The C-index was 0.60 (95% CI 0.53-0.67) for both Sarculator and PERSARC. The MPNST-specific model had a pooled C-index of 0.69 (95%CI 0.65-0.73) at validation, with adequate discrimination and calibration across regions. Conclusions: The MPNST-specific MONACO model can be used to predict 3-, 5-, and 10-year OS in patients with primary MPNST who underwent macroscopically complete surgical resection. Further validation may refine the model to inform patients and physicians on prognosis and support them in shared decision-making.

Dynamic Prediction of Overall Survival for Patients with Osteosarcoma: A Retrospective Analysis of the EURAMOS-1 Clinical Trial Data.

Current prediction models for patients with ostosarcoma are restricted to predictions from a single, static point in time, such as diagnosis or surgery. These approaches discard information which becomes available during follow-up and may have an impact on patient's prognosis. This study aims at developing a dynamic prediction model providing 5-year overall survival (OS) predictions from different time points during follow-up. The developed model considers relevant baseline prognostic factors, accounting for where appropriate time-varying effects and time-varying intermediate events such as local recurrence (LR) and new metastatic disease (NM). A landmarking approach is applied to 1965 patients with high-grade resectable osteosarcoma from the EURAMOS-1 trial (NCT00143030). Results show that LR and NM negatively affected 5-year OS (HRs: 2.634, 95% CI 1.845-3.761; 8.558, 95% CI 7.367-9.942, respectively). Baseline factors with strong prognostic value (HRs > 2) included poor histological response (≥10% viable tumor), axial tumor location, and the presence of lung metastases. The effect of poor versus good histological response changed over time, becoming non-significant from 3.25 years post-surgery onwards. This time-varying effect, as well as the strong impact of disease-related time-varying variables, show the importance of including updated information collected during follow-up in the model to provide more accurate survival predictions.

Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation.

PURPOSE: Decision about the optimal timing of a treatment procedure in patients with hematologic neoplasms is critical, especially for cellular therapies (most including allogeneic hematopoietic stem-cell transplantation [HSCT]). In the absence of evidence from randomized trials, real-world observational data become beneficial to study the effect of the treatment timing. In this study, a framework to estimate the expected outcome after an intervention in a time-to-event scenario is developed, with the aim of optimizing the timing in a personalized manner. METHODS: Retrospective real-world data are leveraged to emulate a target trial for treatment timing using multistate modeling and microsimulation. This case study focuses on myelodysplastic syndromes, serving as a prototype for rare cancers characterized by a heterogeneous clinical course and complex genomic background. A cohort of 7,118 patients treated according to conventional available treatments/evidence across Europe and United States is analyzed. The primary clinical objective is to determine the ideal timing for HSCT, the only curative option for these patients. RESULTS: This analysis enabled us to identify the most appropriate time frames for HSCT on the basis of each patient's unique profile, defined by a combination relevant patients' characteristics. CONCLUSION: The developed methodology offers a structured framework to address a relevant clinical issue in the field of hematology. It makes several valuable contributions: (1) novel insights into how to develop decision models to identify the most favorable HSCT timing, (2) evidence to inform clinical decisions in a real-world context, and (3) the incorporation of complex information into decision making. This framework can be applied to provide medical insights for clinical issues that cannot be adequately addressed through randomized clinical trials.

Clinical and Genomic-Based Decision Support System to Define the Optimal Timing of Allogeneic Hematopoietic Stem-Cell Transplantation in Patients With Myelodysplastic Syndromes.

PURPOSE: Allogeneic hematopoietic stem-cell transplantation (HSCT) is the only potentially curative treatment for patients with myelodysplastic syndromes (MDS). Several issues must be considered when evaluating the benefits and risks of HSCT for patients with MDS, with the timing of transplantation being a crucial question. Here, we aimed to develop and validate a decision support system to define the optimal timing of HSCT for patients with MDS on the basis of clinical and genomic information as provided by the Molecular International Prognostic Scoring System (IPSS-M). PATIENTS AND METHODS: We studied a retrospective population of 7,118 patients, stratified into training and validation cohorts. A decision strategy was built to estimate the average survival over an 8-year time horizon (restricted mean survival time [RMST]) for each combination of clinical and genomic covariates and to determine the optimal transplantation policy by comparing different strategies. RESULTS: Under an IPSS-M based policy, patients with either low and moderate-low risk benefited from a delayed transplantation policy, whereas in those belonging to moderately high-, high- and very high-risk categories, immediate transplantation was associated with a prolonged life expectancy (RMST). Modeling decision analysis on IPSS-M versus conventional Revised IPSS (IPSS-R) changed the transplantation policy in a significant proportion of patients (15% of patient candidate to be immediately transplanted under an IPSS-R-based policy would benefit from a delayed strategy by IPSS-M, whereas 19% of candidates to delayed transplantation by IPSS-R would benefit from immediate HSCT by IPSS-M), resulting in a significant gain-in-life expectancy under an IPSS-M-based policy (P = .001). CONCLUSION: These results provide evidence for the clinical relevance of including genomic features into the transplantation decision making process, allowing personalizing the hazards and effectiveness of HSCT in patients with MDS.

Novel longitudinal Multiple Overall Toxicity (MOTox) score to quantify adverse events experienced by patients during chemotherapy treatment: a retrospective analysis of the MRC BO06 trial in osteosarcoma.

OBJECTIVES: This study aims at exploring and quantifying multiple types of adverse events (AEs) experienced by patients during cancer treatment. A novel longitudinal score to evaluate the Multiple Overall Toxicity (MOTox) burden is proposed. The MOTox approach investigates the personalised evolution of high overall toxicity (high-MOTox) during the treatment. DESIGN: Retrospective analysis of the MRC-BO06/EORTC-80931 randomised controlled trial for osteosarcoma. SETTING: International multicentre population-based study. PARTICIPANTS: A total of 377 patients with resectable high-grade osteosarcoma, who completed treatment within 180 days after randomisation without abnormal dosages (+25% higher than planned). INTERVENTIONS: Patients were randomised to six cycles of conventional versus dose-intense regimens of doxorubicin and cisplatin. Non-haematological toxicity data were collected prospectively and graded according to the Common Terminology Criteria for Adverse Events (CTCAE). MAIN OUTCOME MEASURES: The MOTox score described the overall toxicity burden in terms of multiple toxic AEs, maximum-severity episode and cycle time-dimension. Evolution of high-MOTox was assessed through multivariable models, that investigated the impact of personalised characteristics (eg, achieved chemotherapy dose, previous AEs or biochemical factors) cycle-by-cycle. RESULTS: A cycle-by-cycle analysis identifies different evolutions of MOTox levels during treatment, detecting differences in patients' health. Mean MOTox values and percentages of patients with high-MOTox decreased cycle-by-cycle from 2.626 to 1.953 and from 57.8% to 36.6%, respectively. High-MOTox conditions during previous cycles were prognostic risk factors for a new occurrence (ORs range from 1.522 to 4.439), showing that patient's history of toxicities played an important role in the evolution of overall toxicity burden during therapy. Conventional regimen may be preferred to dose-intense in terms of AEs at cycles 2-3 (p<0.05). CONCLUSIONS: The novel longitudinal method developed can be applied to any cancer studies with CTCAE-graded toxicity data. After validation in other studies, the MOTox approach may lead to improvements in healthcare assessment and treatment planning. TRIAL REGISTRATION NUMBER: ISRCTN86294690; Post-results.

Functional modeling of recurrent events on time-to-event processes.

In clinical practice, it is often the case where the association between the occurrence of events and time-to-event outcomes is of interest; thus, it can be modeled within the framework of recurrent events. The purpose of our study is to enrich the information available for modeling survival with relevant dynamic features, properly taking into account their possibly time-varying nature, as well as to provide a new setting for quantifying the association between time-varying processes and time-to-event outcomes. We propose an innovative methodology to model information carried out by time-varying processes by means of functional data, modeling each time-varying variable as the compensator of marked point process the recurrent events are supposed to derive from. By means of Functional Principal Component Analysis, a suitable dimensional reduction of these objects is carried out in order to plug them into a Cox-type functional regression model for overall survival. We applied our methodology to data retrieved from the administrative databases of Lombardy Region (Italy), related to patients hospitalized for Heart Failure (HF) between 2000 and 2012. We focused on time-varying processes of HF hospitalizations and multiple drugs consumption and we studied how they influence patients' overall survival. This novel way to account for time-varying variables allowed to model self-exciting behaviors, for which the occurrence of events in the past increases the probability of a new event, and to quantify the effect of personal behaviors and therapeutic patterns on survival, giving new insights into the direction of personalized treatment.

Dynamic monitoring of the effects of adherence to medication on survival in heart failure patients: A joint modeling approach exploiting time-varying covariates.

Adherence to medication is the process by which patients take their drugs as prescribed, and represents an issue in pharmacoepidemiological studies. Poor adherence is often associated with adverse health conditions and outcomes, especially in case of chronic diseases such as heart failure (HF). This turns out in an increased request for health care services, and in a greater burden for the health care system. In recent years, there has been a substantial growth in pharmacotherapy research, aimed at studying effects and consequences of proper/improper adherence to medication both for the increasing awareness of the problem and for the pervasiveness of poor adherence among patients. However, the way adherence is computed and accounted for into predictive models is far from being informative as it may be. In fact, it is usually analyzed as a fixed baseline covariate, without considering its time-varying behavior. The purpose and novelty of this study is to define a new personalized monitoring tool exploiting time-varying definition of adherence to medication, within a joint modeling approach. In doing so, we are able to capture and quantify the association between the longitudinal process of dynamic adherence to medication with the long-term survival outcome. Another novelty of this approach consists of exploiting the potential of health care administrative databases in order to reconstruct the dynamics of drugs consumption through pharmaceutical administrative registries. In particular, we analyzed administrative data provided by Regione Lombardia - Healthcare Division related to patients hospitalized for HF between 2000 and 2012.

Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study.

BACKGROUND: Much data about prescription adherence in patients with heart failure (HF) are available, but few exist about the evaluation of true patient adherence. Further, methods for analyzing this issue are poorly known. OBJECTIVES: Our objective was to evaluate the impact of patient adherence to disease-modifying drugs after HF hospitalization in a community-based cohort. METHODS AND RESULTS: Patients hospitalized with first diagnostic HF code and at least one post-discharge purchase of evidence-based drugs for HF between 2009 and 2015 were included (12,938 patients). A new method for measuring adherence to polypharmacy (patient adherence indicator [PAI]) was introduced, based on proportion of days covered (PDC) and medication possession ratio (MPR). The investigated drugs were ß-blockers (BBs), angiotensin-converting enzyme inhibitors (ACEIs), angiotensin-receptor blockers (ARBs), and anti-aldosterone agents (AAs). Regional administrative databases were analyzed. RESULTS: The mean age of the cohort was 80 years; 53% was female; the median Charlson Comorbidity Index score was 2, and the overall death rate was 60%. PAI based on PDC estimated a nonadherence rate of 47%. Median daily dosages were well below target dosages for all drugs considered. A good PAI significantly lowered the mortality risk, irrespective of the computational method used: PDC (PAI adjusted hazard ratio [HR] 0.93; 95% confidence interval [CI] 0.88-0.97; p = 0.001) or MPR (PAI adjusted HR 0.93; 95% CI 0.89-0.98; p = 0.004). CONCLUSIONS: In a real-world setting, medication adherence of patients with HF remains unsatisfactory, especially when in a polypharmacy setting. Irrespective of PDC and MPR, good patient adherence to polypharmacy was associated with a lower death rate.

One size doesn't fit all: Should we reconsider the introduction of cold-stored platelets in blood bank inventories?

Platelet concentrates are universally prepared with a standard method and stored for 5 days at room temperature (20-24°C) in gentle agitation. Currently, there is a renewed interest in the possibility of storing platelet concentrates below the standard temperatures. In fact, cold platelets might be more effective in bleeding patients and have a lower risk of bacterial transmission. Inventories including platelets at different temperatures may favour patient-centred strategies for prophylactic or therapeutic transfusions.

Lack of Siglec-7 expression identifies a dysfunctional natural killer cell subset associated with liver inflammation and fibrosis in chronic HCV infection.

OBJECTIVE: Sialic-acid-binding immunoglobulin-like lectin-7 (Siglec-7) is a natural killer (NK) cell inhibitory receptor associated with NK phenotypic and functional abnormalities in HIV-1 infection. We investigated the significance of NK-expressed and serum soluble Siglec-7 in relation to NK functional ability and parameters of liver necroinflammation and fibrosis in chronic HCV infection. DESIGN: NK-expressed and serum Siglec-7 were evaluated in 130 and 166 HCV-infected individuals by flow cytometry and ELISA, respectively. NK cell degranulation and cytokine secretion were determined by flow cytometry. 65 patients with chronic HBV infection, 84 with chronic biliary disorders and 168 healthy donors served as controls. RESULTS: Expression of Siglec-7 was significantly decreased on NK cells from HCV-infected and HBV-infected patients and, conversely, serum Siglec-7 was significantly increased in these patients compared with controls. The frequency of Siglec-7pos NK cells was significantly higher at baseline in sustained virological responders to pegylated interferon-α/ribavirin treatment than in non-responders. Activating receptor expression was significantly higher in Siglec-7pos NK cells and was associated with increased degranulation and cytokine secretion compared with Siglec-7neg cells. In chronic HCV infection, there was an inverse correlation between Siglec-7 expression and serum aminotransferases, γ-glutamyl transpeptidase, liver stiffness, aspartate aminotransferase to platelet ratio index and fibrosis-4 scores, and a positive correlation between serum Siglec-7 and the same clinical parameters, including histological staging. CONCLUSIONS: These findings identify Siglec-7neg NK cells as a dysfunctional subpopulation associated with severe liver disease in chronic HCV infection.

Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes.

Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

Poor efficacy of nucleic acid testing in identifying occult HBV infection and consequences for safety of blood supply in Italy.

BACKGROUND & AIMS: In Italy, DNA screening of blood donations for hepatitis B virus (HBV) was introduced to prevent the transmission of window period and occult HBV infection. Anti-HBc screening is not recommended in order to avoid shortage of the blood supply. To contain costs, donor samples are generally pooled before testing. We evaluated the safety of this national policy using a prospective repository of donors/recipient pairs. METHODS: We used highly sensitive nucleic acid testing (NAT) assays to test repository and follow-up samples from donors who were initially classified as negative by minipool NAT assays (6-MP), but were later found to carry occult HBV DNA. When available, we also analysed recipients' pre- and post-transfusion samples, collected in the context of a repository financed by the European Commission (the BOTIA project). RESULTS: Between 2008 and 2011 6-MP NAT assays identified 18 carriers of occult HBV infection among 12,695 donors; 28 samples from previous donations were available from 13 of these carriers. Highly sensitive HBV DNA detection methods showed that 6-MP HBV DNA screening failed to identify 14/28 (50%) viraemic donations, that were released for transfusion. HBV marker testing of such blood product recipients revealed two cases of transfusion transmitted HBV infection, documented by donor-recipient sequence identity. CONCLUSIONS: Viraemic blood donations from occult HBV infection carriers remain undetected by current minipool HBV DNA screening, and transfusion transmission of HBV continues to occur in susceptible patients. More effective individual HBV DNA screening and/or tests for antibodies to HBV core antigen should be considered to improve blood safety.

Plasmodium genome in blood donors at risk for malaria after several years of residence in Italy.

BACKGROUND: At present, the main risk of transfusion-transmitted malaria (TTM) in nonendemic countries is chronic, asymptomatic immigrants from malaria-endemic areas. Semi-immune donors may carry undetected parasitemia. This study examines Plasmodium infection in at-risk blood donors in Northern Italy. STUDY DESIGN AND METHODS: Plasma samples from 97 candidate donors and 80 controls were tested for malarial antibodies using a commercial enzyme immunoassay. The conserved 18S rRNA and the mitochondrial genes of Plasmodium were amplified to detect and quantify parasite genomes (copies/mL). Plasmodium species were identified with a species-specific nested polymerase chain reaction. Parasitemic samples were further tested by amplification of polymorphic repetitive regions in MSP-1 Block 2, MSP-2 Block 3, and glutamate-rich protein (GLURP) confirmed by sequencing. RESULTS: Three of 83 seropositive (3.6%) and one of 14 seronegative at-risk candidate donors carried Plasmodium genome (4 × 10(3) -8.5 × 10(4) copies/mL): two P. falciparum, one P. malariae (seronegative sample), and one coinfection with P. malariae and P. ovale. Alleles of MSP-1 (MAD20 and K1), MSP-2 (3D7 and FC27), and GLURP were amplified from Sample 261. In Sample 282 only one allele in MSP-2 (FC27) and GLURP was amplified. No alleles were detected in Samples 283 and 331. CONCLUSIONS: Immigrants from endemic countries might carry infectious Plasmodium after 2 to 5 years of continuous residence in Italy. Serologic screening may miss donors carrying P. malariae. Permanent exclusion or screening for both antibodies and genome are needed to prevent TTM.

High serum levels of HDV RNA are predictors of cirrhosis and liver cancer in patients with chronic hepatitis delta.

Chronic infection with the hepatitis delta virus (HDV) is a risk factor for cirrhosis and hepatocellular carcinoma (HCC), but little is known whether the outcome of hepatitis is predicted by serum markers of HDV and hepatitis B virus (HBV) infection. The aim of the study was to investigate these correlations in 193 patients with chronic HDV infection who had been followed up for a median of 9.5 years (4.8-19.3). HDV-RNA was first measured by qualitative in-house nested RT-PCR and quantified by in-house real-time PCR. HDV RNA levels only appeared significantly associated to HCC (univariate analysis: OR 1.32, 95% CI 1.02-1.71; p = 0.037; multivariate analysis: OR 1.42, 95% CI 1.04-1.95; p = 0.03). In non-cirrhotics at first presentation (n = 105), HDV RNA levels were associated with progression to cirrhosis (univariate analysis: OR = 1.57, 95% CI 1.20-2.05, p<0.001; multivariate analysis: OR = 1.60, 95% CI 1.20-2.12, p = 0.007) and development of HCC (univariate analysis: OR = 1.66, 95% CI 1.04-2.65, p = 0.033; multivariate analysis: OR = 1.88, 95% CI 1.11-3.19, p = 0.019). ROC analysis showed that approximately 600,000 HDV RNA copies/mL was the optimal cut-off value in our cohort of patients for discriminating the development of cirrhosis. High levels of HDV viremia in non-cirrhotic patients are associated with a considerable likelihood of progression to cirrhosis and the development of HCC. Once cirrhosis has developed, the role of HDV replication as a predictor of a negative outcome lessens.

Evidence of distinct tumour-propagating cell populations with different properties in primary human hepatocellular carcinoma.

BACKGROUND AND AIMS: Increasing evidence that a number of malignancies are characterised by tumour cell heterogeneity has recently been published, but there is still a lack of data concerning liver cancers. The aim of this study was to investigate and characterise tumour-propagating cell (TPC) compartments within human hepatocellular carcinoma (HCC). METHODS: After long-term culture, we identified three morphologically different tumour cell populations in a single HCC specimen, and extensively characterised them by means of flow cytometry, fluorescence microscopy, karyotyping and microarray analyses, single cell cloning, and xenotransplantation in NOD/SCID/IL2Rγ/⁻ mice. RESULTS: The primary cell populations (hcc-1, -2 and -3) and two clones generated by means of limiting dilutions from hcc-1 (clone-1/7 and -1/8) differently expressed a number of tumour-associated stem cell markers, including EpCAM, CD49f, CD44, CD133, CD56, Thy-1, ALDH and CK19, and also showed different doubling times, drug resistance and tumorigenic potential. Moreover, we found that ALDH expression, in combination with CD44 or Thy-1 negativity or CD56 positivity identified subpopulations with a higher clonogenic potential within hcc-1, hcc-2 and hcc-3 primary cell populations, respectively. Karyotyping revealed the clonal evolution of the cell populations and clones within the primary tumour. Importantly, the primary tumour cell population with the greatest tumorigenic potential and drug resistance showed more chromosomal alterations than the others and contained clones with epithelial and mesenchymal features. CONCLUSIONS: Individual HCCs can harbor different self-renewing tumorigenic cell types expressing a variety of morphological and phenotypical markers, karyotypic evolution and different gene expression profiles. This suggests that the models of hepatic carcinogenesis should take into account TPC heterogeneity due to intratumour clonal evolution.

Influence of 9p21.3 genetic variants on clinical and angiographic outcomes in early-onset myocardial infarction.

OBJECTIVES: The purpose of this study was to test whether the 9p21.3 variant rs1333040 influences the occurrence of new cardiovascular events and coronary atherosclerosis progression after early-onset myocardial infarction. BACKGROUND: 9p21.3 genetic variants are associated with ischemic heart disease, but it is not known whether they influence prognosis after an acute coronary event. METHODS: Within the Italian Genetic Study of Early-onset Myocardial Infarction, we genotyped rs1333040 in 1,508 patients hospitalized for a first myocardial infarction before the age of 45 years who underwent coronary angiography without index event coronary revascularization. They were followed up for major cardiovascular events and angiographic coronary atherosclerosis progression. RESULTS: Over 16,599 person-years, there were 683 cardiovascular events and 492 primary endpoints: 77 cardiovascular deaths, 223 reoccurrences of myocardial infarction, and 383 coronary artery revascularizations. The rs1333040 genotype had a significant influence (p = 0.01) on the primary endpoint, with an adjusted hazard ratio of 1.19 (95% confidence interval [CI]: 1.08 to 1.37) for heterozygous carriers and 1.41 (95% CI: 1.06 to 1.87) for homozygous carriers. Analysis of the individual components of the primary endpoints provided no significant evidence that the rs1333040 genotype influenced the hazard of cardiovascular death (p = 0.24) or the reoccurrence of myocardial infarction (p = 0.57), but did provide significant evidence that it influenced on the hazard of coronary revascularization, with adjusted heterozygous and homozygous ratios of 1.38 (95% CI: 1.17 to 1.63) and 1.90 (95% CI: 1.36 to 2.65) (p = 0.00015), respectively. It also significantly influenced the angiographic endpoint of coronary atherosclerosis progression (p = 0.002). CONCLUSIONS: In early-onset myocardial infarction, the 9p21.3 variant rs1333040 affects the progression of coronary atherosclerosis and the probability of coronary artery revascularization during long-term follow-up.