The use of the Joint Models to improve the accuracy of prognostication of death in patients with heart failure and reduced ejection fraction (HFrEF)

The work presented in this thesis has been developed during a scholarship at the Scientific Directorate - Unit of Biostatistics of the Galliera Hospital in Genoa under the supervision of Dr. Matteo Puntoni. This scholarship was partially supported by a grant from Ministry of Health, Italy "Bando Ricerca Finalizzata - Giovani Ricercatori" (Project code: GR-2013-02355479) won by Dr. Puntoni for conducting a cancer research study. The main objective of my research was to apply the Joint Model for longitudinal and survival data to improve the dynamic prediction of cardiovascular diseases in patients undergoing cancer treatment. These patients are usually followed after the start of the therapy with several visits in the course of which different longitudinal data are collected. These data are usually collected and interpreted by clinicians but not in a systematic way. The innovation of my project consisted in a more formal use of these data in a statistical model. The Joint Model is essentially based on the simultaneous modelling of a linear mixed model for longitudinal data and a survival model for the probability of an event. The utility of this model is twofold: on one hand it links the change of a longitudinal measurement to a change in the risk of an event, on the other hand the prediction of survival probabilities using the Joint Model can be updated whenever a new measurement is taken. Unfortunately, the clinical study on cancer therapy for which the project was thought is still ongoing at this moment and the longitudinal data are not available. So, we applied the developed methods based on Joint Model to another dataset with a similar clinical interest. The case of study presented in the Chapter 6 of this thesis is developed after a meeting between Dr. Puntoni and me and Dr. Marco Canepa of the Cardiovascular Disease Unit of the San Martino Hospital in Genoa. The necessity of the last one was to prove that the longitudinal data collected in patients after a heart failure could be used to improve the prognostication of death and, more in general, the patient management and care with a personalized therapy. The last one could be better calibrated by a dynamic update of the prognosis of patients related to a better analysis of the longitudinal data provided during each follow-up visit. The Joint Model for longitudinal and survival data solves the problem of the simultaneous analysis of the biomarkers collected at each follow-up visits and the dynamic update of the survival probabilities each time a new measurements are collected (see Chapter 4). The next step, developed in the Chapter 5, was to find a statistical index that was simple to understand and practical for clinicians but also methodologically adequate to assess and prove that the longitudinal data are advantage in the prognostication of death. To do this, two different indexes seemed most suitable: the area under the Receiver Operating Characteristic Curve (AUC-ROC) to assess the prediction capability of the Joint Model, and the Net Reclassification Improvement (NRI) to evaluate the improvement in prognostication in comparison with other approaches commonly used in clinical studies. In Section 5.3, a new definition of time-dependent AUC-ROC and time-dependent NRI in the Joint Model context is given. Even if a function to derive the AUC after a Joint Model was present in literature, we needed to reformulate it and implement in the statistical software R to make it comparable with the index derived after the use of the common survival models, such as the Weibull Model. Regarding the NRI, no indexes are present in the literature. Some methods and functions were developed for binary and survival context but no one for the Joint Model. A new definition of time-dependent NRI is presented in Section 5.3.2 and used to compare the common Weibull survival model and the Joint Model. This thesis is divided in 6 chapters. Chapters 1 and 2 are preparatory to the introduction of the Joint Model in Chapter 3. In particular, Chapter 1 is an introduction to the analysis of longitudinal data with the use of Linear Mixed Models while Chapter 2 presents concepts and models used in the thesis from survival analysis. In Chapter 3 the elements introduced in the first two chapters are joined to defined the Joint Model for longitudinal and survival data following the approach proposed by Rizopoulos (2012). Chapter 4 introduces the main ideas behind dynamic prediction in the Joint Model context. In Chapter 5 relevant notions of prediction capability are introduced in relation to the indexes AUC and NRI. Initially, these two indexes are presented in relation to a binary outcome. Then, it is shown how they change when the outcome is the time to an event of interest. Ending, the definitions of time-dependent AUC and NRI are formulated in the Joint Model context. The case of study is presented in the Chapter 6 along with strength and limitations related to the use of the Joint Model in clinical studies

The Multidimensional Prognostic Index in general practice: One-year follow-up study.

BACKGROUND Older patients' health problems in general practice (GP) can often not be assigned to a specific disease, requiring a paradigm shift to goal-oriented, personalised care for clinical decision making. PURPOSE To investigate the predictive value of the comprehensive geriatric assessment (CGA)-based Multidimensional Prognostic Index (MPI) in a GP setting with respect to the main healthcare indicators during the 12 months following initial evaluation. METHODS One hundred twenty-five consecutive patients aged 70 years and older were enrolled in a GP and followed up to one year. All patients underwent a CGA based on which the MPI was calculated and subdivided into three risk groups (MPI-1, 0-0.33 = low risk, MPI-2, 0.34-0.66 = moderate risk and MPI-3, 0.67-1, severe risk). Grade of Care (GC), hospitalization rate, mortality, nursing home admission, use of home care services, falls, number of general practitioner contacts (GPC), of geriatric resources (GR) and geriatric syndromes (GS) during the 12 months following initial evaluation were collected. RESULTS The MPI was significantly associated with number of GS (P < .001), GR (P < .001), GC (P < .001) as well as with the average number of GPC per year (mean 10.4, P = .046). Interestingly, the clinical judgement of the general practitioner, in this case knowing his patients for 16 years on average, was associated with adverse outcomes to a similar extent than the prediction offered by the MPI (GP/adverse outcomes and MPI/adverse outcomes P < .001). CONCLUSION The MPI is strongly associated with adverse outcomes in older GP patients and strongly predicts the number of GPC up to one year after initial evaluation. Considering the feasibility and the strong clinimetric properties of the MPI, its collection should be encouraged as early as possible to disclose risk conditions, implement tailored preventive strategies and improve cost-effectiveness of healthcare resources use

Cross-national variation in the association between family structure and overweight and obesity: Findings from the Health Behaviour in School-aged children (HBSC) study

Background Trends of increased complexity in family structure have developed alongside increasing prevalence of overweight and obesity. This study examines cross-national variations in the likelihood of living with overweight and obesity among adolescents living with one parent versus two parents, as well as the influence of living with stepparents, grandparents and siblings. Furthermore, the study explores how these associations relate to age, gender and individual-level socioeconomic status (SES) and country-level SES. We hypothesised that adolescents living in one-parent versus two-parents families, were more likely to live with overweight and obesity. Methods The study is based on nationally representative data from 41 countries participating in the 2013/14 Health Behaviors in School-Aged Children study (n = 211.798). Multilevel logistic regression analysis was used to examine the associations between family structure and overweight and obesity by age, gender, SES, and geographic region, among adolescents aged 11, 13 and 15 years. Results Living with one versus two parent(s) was associated with a higher likelihood of overweight and obesity (ORadj.1.13, 95%CI 1.08,1.17). Age, gender, individual-level SES, and living with grandparents were also associated with a higher likelihood of overweight and obesity, whereas living with siblings was associated with a lower likelihood of overweight and obesity. The effect of family structure varied also by age and gender with no significant associations found between living with one parent and overweight and obesity in the 15-year-old age group. Some cross-national variation was observed, and this was partly explained by country-level SES. The effect of family structure increased by a factor 1.08 per one-unit change in country-level SES (OR 1.08, 95%CI1.03, 1.12). Conclusion The study indicates that living in a one-parent family, as well as living together with grandparents, are associated with overweight and obesity among adolescents, particularly in the Nordic European region. Existing welfare policies may be insufficient to eliminate inequalities related to family structure differences.publishedVersio

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P &lt; 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Aromatase Inhibitors as Adjuvant Treatment for ER/PgR Positive Stage I Endometrial Carcinoma: A Retrospective Cohort Study

Objective: Although endometrial cancer (EC) is a hormone dependent neoplasm, there are no recommendations for the determination of steroid hormone receptors in the tumor tissue and no hormone therapy has ever been assessed in the adjuvant setting. The purpose of this study was to explore the effect of adjuvant aromatase inhibitors (AIs) on progression-free survival (PFS) and overall survival (OS) in patients with early stage and steroid receptors-positive EC. Methods: We retrospectively analyzed clinical and pathological factors in 73 patients with high-risk (49.3%) or low-risk (50.7%) stage I (n = 71) or II (n = 2) endometrial cancer who received by their preference after counseling either no treatment (reference group) or AI. Prognostic factors were well balanced between groups. Expression of estrogen receptor (ER), progesterone receptor (PgR), and Ki-67 index was correlated with clinical outcomes. Results: Univariate and multivariate Cox proportional regression analyses, adjusted for age, grade, stage, depth of myometrial invasion, lymphovascular space invasion, BMI, ER, PgR and Ki-67 labeling index levels, showed that PFS and OS had a trend to be longer in patients receiving AI than in the reference group HR= 0.23 (95% CI; 0.04&ndash;1.27) for PFS and HR= 0.11 (95% CI; 0.01&ndash;1.36) for OS. Conclusion: Compared with no treatment, AI exhibited a trend toward a benefit on PFS and OS in patients with early stage hormone receptor-positive EC. Given the exploratory nature of our study, randomized clinical trials for ER/PgR positive EC patients are warranted to assess the clinical benefit of AI and the potential predictive role of steroid receptors and Ki-67

The prognostic significance of geriatric syndromes and resources

Background Geriatric syndromes (GS) do not fit into discrete disease categories and are often underdiagnosed in hospitalized older adults. Geriatric resources (GR) are also not routinely collected in clinical settings, although this may potentiate the beneficial effects of clinical decisions. The prognostic relevance of GS and GR has never been systematically evaluated through clinical tools developed for clinical decision purposes. Aim To ascertain the impact of common GS and GR on patients' prognosis as assessed by means of the comprehensive geriatric assessment (CGA)-based Multidimensional Prognostic Index (MPI). Methods One hundred and thirty-five hospitalized patients aged 70 years and older underwent a CGA evaluation with calculation of the MPI on admission and discharge. Accordingly, patients were subdivided in low (MPI-1, score 0-0.33), moderate (MPI-2, score 0.34-0.66), and severe (MPI-3, score 0.67-1)-risk of mortality at 1 month and 1 year. Nine GR and 17 GS were identified and collected accordingly. Results A lower number of GS and a higher number of GR were shown to be highly significantly correlated with a lower MPI, as well as years of education, grade of care, and number of medications independent of age, sex and number of GS or GR. Underweight and obesity according to the BMI were significantly correlated to higher number of GS. Patients with more GR had a significantly higher chance of being discharged home. Conclusions The MPI evaluation together with GS and GR in acute care for older patients should be encouraged to improve clinical decision-making

New associations of the Multidimensional Prognostic Index

Background The multidimensional prognostic index (MPI) is a validated, sensitive, and specific prognosis estimation tool based on a comprehensive geriatric assessment (CGA). The MPI accurately predicts mortality after 1 month and 1 year in older, multimorbid patients with acute disease or relapse of chronic conditions. Objective To evaluate whether the MPI predicts indicators of healthcare resources, i.e. grade of care (GC), length of hospital stay (LHS) and destination after hospital discharge in older patients in an acute medical setting. Material and methods In this study 135 hospitalized patients aged 70 years and older underwent a CGA evaluation to calculate the MPI on admission and discharge. Accordingly, patients were subdivided in low (MPI-1, score 0-0.33), moderate (MPI-2, score 0.34-0.66) and high (MPI-3, score 0.67-1) risk of mortality. The GC, LHS and the discharge allocation were also recorded. Results The MPI score was significantly related to LHS (p= 0.011) and to GC (p< 0.001). In addition, MPI-3 patients were significantly more often transferred from other hospital settings (p= 0.007) as well as significantly less likely to be discharged home (p= 0.04) than other groups. Conclusion The CGA-based MPI values are significantly associated with use of indicators of healthcare resources, including GC, LHS and discharge allocation. These findings suggest that the MPI may be useful for resource planning in the care of older multimorbid patients admitted to hospital