General Population Mortality Adjustment in Survival Extrapolation of Cancer Trials: Exploring Plausibility and Implications for Cost-Effectiveness Analyses in HER2-Positive Breast Cancer in Sweden.

BACKGROUND: In economic evaluations of novel therapies, assessing lifetime effects based on trial data often necessitates survival extrapolation, with the choice of model affecting outcomes. The aim of this study was to assess accuracy and variability between alternative approaches to survival extrapolation. METHODS: Data on HER2-positive breast cancer patients from the Swedish National Breast Cancer Register were used to fit standard parametric distribution (SPD) models and excess hazard (EH) models adjusting the survival projections based on general population mortality (GPM). Models were fitted using 6-y data for stage I and II, 4-y data for stage III, and 2-y data for stage IV cancer reflecting an early data cutoff while maintaining sufficient events for comparison of model estimates with actual long-term outcomes. We compared model projections of 15-y survival and restricted mean survival time (RMST) to 15-y registry data and explored the variability between models in extrapolations of long-term survival. RESULTS: Among 11,224 patients compared with the observed registry 15-y RMST estimates across the disease stages, EH cure models provided the most accurate estimates in patients with stage I to III cancer, whereas EH models without cure most closely matched survival in patients with stage IV cancer, in which cure assumption was less plausible. The Akaike information criterion-averaged model projections varied as follows: -8.2% to +5.3% for SPD models, -4.9% to +5.2% for the EH model without a cure assumption, and -19.3% to -0.2% for the EH model with a cure assumption. EH models significantly reduced between-model variance in the predicted RMSTs over a 50-y time horizon compared with SPD models. CONCLUSIONS: EH models may be considered as alternatives to SPD models to produce more accurate and plausible survival extrapolation that accounts for general population mortality. HIGHLIGHTS: Excess hazard (EH) methods have been suggested as an approach to incorporate background mortality rates in economic evaluation using survival extrapolation.We highlight that EH models with or without a cure assumption can produce more accurate survival projections and significantly reduce between-model variability in comparison with standard parametric distribution models across cancer stages.EH models may be a preferred modeling method to reduce model uncertainty in health economic modeling since models that would otherwise have produced implausible extrapolations are constrained by the EH framework.Reduced uncertainty in economic evaluations will enhance the application of evidence-based health care decision making.

Prognostic Role of Clinicopathological Characteristics and Serum Markers in Metastatic Melanoma Patients Treated with BRAF and MEK Inhibitors.

Prognostic studies can provide important information about disease biology and improve the use of biomarkers to optimize treatment decisions. METHODS: A total of 199 patients with advanced melanoma treated with BRAF + MEK inhibitors were included in our single-center retrospective study. We analyzed the risk of progression and death using multivariate Cox proportional hazard models. The predictive effect of prognostic factors on progression-free survival (PFS) was evaluated in ROC analysis. RESULTS: We found that primary tumor localization, Clark level, pT category, baseline M stage and baseline serum S100B are independent and significant prognostic factors for PFS. The discriminative power of the combination of these factors was excellent for predicting 18 month PFS (AUC 0.822 [95% CI 0.727; 0.916], p < 0.001). Primary tumor localization on the extremities, Clark level V, baseline M1c stage or M1d stage, and elevated baseline serum S100B and LDH levels were independently and significantly associated with unfavorable overall survival (OS). CONCLUSION: Baseline M stage and serum S100B appear to be independent prognostic factors for both PFS and OS in melanoma patients treated with BRAF + MEK inhibitors. We newly identified significant and independent prognostic effects of primary tumor localization and Clark level on survival that warrant further investigation.

Influence of donor age on liver transplantation outcomes: A multivariate analysis and comparative study.

BACKGROUND: The growing disparity between the rising demand for liver transplantation (LT) and the limited availability of donor organs has prompted a greater reliance on older liver grafts. Traditionally, utilizing livers from elderly donors has been associated with outcomes inferior to those achieved with grafts from younger donors. By accounting for additional risk factors, we hypothesize that the utilization of older liver grafts has a relatively minor impact on both patient survival and graft viability. AIM: To evaluate the impact of donor age on LT outcomes using multivariate analysis and comparing young and elderly donor groups. METHODS: In the period from April 2013 to December 2018, 656 adult liver transplants were performed at the University Hospital Merkur. Several multivariate Cox proportional hazards models were developed to independently assess the significance of donor age. Donor age was treated as a continuous variable. The approach involved univariate and multivariate analysis, including variable selection and assessment of interactions and transformations. Additionally, to exemplify the similarity of using young and old donor liver grafts, the group of 87 recipients of elderly donor liver grafts (≥ 75 years) was compared to a group of 124 recipients of young liver grafts (≤ 45 years) from the dataset. Survival rates of the two groups were estimated using the Kaplan-Meier method and the log-rank test was used to test the differences between groups. RESULTS: Using multivariate Cox analysis, we found no statistical significance in the role of donor age within the constructed models. Even when retained during the entire model development, the donor age's impact on survival remained insignificant and transformations and interactions yielded no substantial effects on survival. Consistent insignificance and low coefficient values suggest that donor age does not impact patient survival in our dataset. Notably, there was no statistical evidence that the five developed models did not adhere to the proportional hazards assumption. When comparing donor age groups, transplantation using elderly grafts showed similar early graft function, similar graft (P = 0.92), and patient survival rates (P = 0.86), and no significant difference in the incidence of postoperative complications. CONCLUSION: Our center's experience indicates that donor age does not play a significant role in patient survival, with elderly livers performing comparably to younger grafts when accounting for other risk factors.

Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials.

Although engineered nanomaterials (ENMs) have tremendous potential to generate technological benefits in numerous sectors, uncertainty on the risks of ENMs for human health and the environment may impede the advancement of novel materials. Traditionally, the risks of ENMs can be evaluated by experimental methods such as environmental field monitoring and animal-based toxicity testing. However, it is time-consuming, expensive, and impractical to evaluate the risk of the increasingly large number of ENMs with the experimental methods. On the contrary, with the advancement of artificial intelligence and machine learning, in silico methods have recently received more attention in the risk assessment of ENMs. This review discusses the key progress of computational nanotoxicology models for assessing the risks of ENMs, including material flow analysis models, multimedia environmental models, physiologically based toxicokinetics models, quantitative nanostructure-activity relationships, and meta-analysis. Several challenges are identified and a perspective is provided regarding how the challenges can be addressed.

Direct and indirect impact of the COVID-19 pandemic on the survival of kidney transplant recipients: A national observational study in France.

During the pandemic period, health care systems were substantially reorganized for managing COVID-19 cases. Corresponding consequences on persons with chronic diseases remain insufficiently documented. This observational cohort study investigated the direct and indirect impact of the pandemic period on the survival of kidney transplant recipients (KTR). Using the French National Health Data System, incident persons with end-stage kidney disease between 2015 and 2020, and who received a kidney transplant during this period were included and followed up from their transplantation date to December 31, 2021. The survival of KTR during the prepandemic and pandemic periods was investigated using Cox models with time-dependent covariates. There were 10 637 KTR included in the study, with 324 and 430 deaths observed during the prepandemic and pandemic periods, respectively. The adjusted risk of death during the pandemic period was similar to that observed during the prepandemic period (hazard ratio [HR] [95% confidence interval]: 0.92 [0.77-1.11]), COVID-19-related hospitalization was associated with an increased risk of death (HR: 10.62 [8.46-13.33]), and a third vaccine dose was associated with a lower risk of death (HR: 0.42 [0.30-0.57]). The pandemic period was not associated with an indirect higher risk of death in KTR with no COVID-19-related hospitalization.

Primary tumour category, site of metastasis, and baseline serum S100B and LDH are independent prognostic factors for survival in metastatic melanoma patients treated with anti-PD-1.

Background: Prognostic classification of metastatic melanoma patients treated with anti-PD-1 is of great interest to clinicians. Objective: We aimed to determine the anti-PD-1 treatment related prognostic performance of demographics, clinical and histological prognostic markers and baseline serum S100B and LDH levels in advanced melanoma. Methods: A total of 200 patients with unresectable metastatic melanoma were included in this retrospective study. 34.5% had stage M1c disease and 11.5% had stage M1d disease at the start of therapy. 30% had pT4b primary melanoma. 55.5% had elevated baseline serum S100B levels and 62.5% had elevated baseline serum LDH levels. We analysed the risk of death using univariate and multivariate Cox proportional-hazards models and the median overall (OS) and progression-free (PFS) survival using the Kaplan-Meier estimator. Results: The median follow-up time from the start of anti-PD-1 treatment in patients who were alive at the end of the study (N=81) was 37 months (range: 6.1-95.9). The multivariate Cox regression analysis showed that M1c stage (vs. M1a, p=0.005) or M1d stage at the start of therapy (vs. M1a, p=0.001), pT4b category (vs. pT1a, p=0.036), elevated baseline serum S100B levels (vs. normal S100B, p=0.008) and elevated LDH levels (vs. normal LDH, p=0.049) were independently associated with poor survival. The combination of M1d stage, elevated baseline serum S100B and LDH levels and pT4b category was associated with a very high risk of death (HR 4.72 [1.81; 12.33]). In the subgroup of patients with pT4b primary melanoma, the median OS of patients with normal serum S100B levels was 37.25 months [95% CI 11.04; 63.46]), while the median OS of patients with elevated serum S100B levels was 8.00 months [95% CI 3.49; 12.51]) (p<0.001); the median OS of patients with normal serum LDH levels was 41.82 months [95% CI 11.33; 72.32]), while the median OS of patients with elevated serum LDH levels was 12.29 months [95% CI 4.35; 20.23]) (p=0.002). Conclusion: Our real-world study indicates that the prognostic role of primary melanoma parameters is preserved in anti-PD-1 treated stage IV patients. Furthermore, there seems to be perspective in combining clinical, histological and serum prognostic markers in a prognostic model.

Colorectal Cancer Survival in German-Danish Border Regions-A Registry-Based Cohort Study.

The aim of this study was (i) to update the reporting of colorectal cancer survival differences over time in the German-Danish border region (Schleswig-Holstein, Southern Denmark, and Zealand) and (ii) to assess the extent to which it can be explained by stage and primary treatment. Incident invasive colorectal cancer cases diagnosed from 2004 to 2016 with a follow-up of vital status through 31 December 2017 were extracted from cancer registries. Analyses were conducted by anatomical subsite and for four consecutive periods. Kaplan-Meier curves and log-rank tests were computed. Cox regression models using data from Schleswig-Holstein from 2004 to 2007 as the reference category were run while controlling for age, sex, stage, and treatment. The cox regression models showed decreasing hazard ratios of death for all three regions over time for both anatomical subsites. The improvement was stronger in the Danish regions, and adjustment for age, sex, stage, and treatment attenuated the results only slightly. In 2014-2016, colon cancer survival was similar across regions, while rectal cancer survival was significantly superior in the Danish regions. Regional survival differences can only partially be explained by differing stage distribution and treatment and may be linked additionally to healthcare system reforms and screening efforts.

Survival Extrapolation Incorporating General Population Mortality Using Excess Hazard and Cure Models: A Tutorial.

BACKGROUND: Different parametric survival models can lead to widely discordant extrapolations and decision uncertainty in cost-effectiveness analyses. The use of excess hazard (EH) methods, which incorporate general population mortality data, has the potential to reduce model uncertainty. This review highlights key practical considerations of EH methods for estimating long-term survival. METHODS: Demonstration of methods used a case study of 686 patients from the German Breast Cancer Study Group, followed for a maximum of 7.3 y and divided into low (1/2) and high (3) grade cancers. Seven standard parametric survival models were fit to each group separately. The same 7 distributions were then used in an EH framework, which incorporated general population mortality rates, and fitted both with and without a cure parameter. Survival extrapolations, restricted mean survival time (RMST), and difference in RMST between high and low grades were compared up to 30 years along with Akaike information criterion goodness-of-fit and cure fraction estimates. The sensitivity of the EH models to lifetable misspecification was investigated. RESULTS: In our case study, variability in survival extrapolations was extensive across the standard models, with 30-y RMST ranging from 7.5 to 14.3 y. Incorporation of general population mortality rates using EH cure methods substantially reduced model uncertainty, whereas EH models without cure had less of an effect. Long-term treatment effects approached the null for most models but at varying rates. Lifetable misspecification had minimal effect on RMST differences. CONCLUSIONS: EH methods may be useful for survival extrapolation, and in cancer, EHs may decrease over time and be easier to extrapolate than all-cause hazards. EH cure models may be helpful when cure is plausible and likely to result in less extrapolation variability. HIGHLIGHTS: In health economic modeling, to help anchor long-term survival extrapolation, it has been recommended that survival models incorporate background mortality rates using excess hazard (EH) methods.We present a thorough description of EH methods with and without the assumption of cure and demonstrate user-friendly software to aid researchers wishing to use these methods.EH models are applied to a case study, and we demonstrate that EHs are easier to extrapolate and that the use of the EH cure model, when cure is plausible, can reduce extrapolation variability.EH methods are relatively robust to lifetable misspecification.

Have recreational marijuana laws undermined public health progress on adult tobacco use?

Public health experts caution that legalization of recreational marijuana may normalize smoking and undermine the decades-long achievements of tobacco control policy. However, very little is known about the impact of recreational marijuana laws (RMLs) on adult tobacco use. Using newly available data from the Population Assessment of Tobacco and Health (PATH) and dynamic difference-in-differences and discrete-time hazard approaches, we find that RML adoption increases prior-month marijuana use among adults ages 18-and-older by 2-percentage-points, driven by an increase in marijuana initiation among prior non-users. However, this increase in adult marijuana use does not extend to tobacco use. Rather, we find that RML adoption is associated with a lagged reduction in electronic nicotine delivery systems (ENDS) use, consistent with the hypothesis that ENDS and marijuana are substitutes. Moreover, auxiliary analyses from the National Survey on Drug Use and Health (NSDUH) show that RML adoption is associated with a reduction in adult cigarette smoking. We conclude that RMLs may generate tobacco-related health benefits.

Effectiveness and cost-effectiveness analysis of 11 treatment paths, seven first-line and three second-line treatments for Chinese patients with advanced wild-type squamous non-small cell lung cancer: A sequential model.

Background: A total of 11 treatment sequences for advanced wild-type squamous non-small cell lung cancer are recommended by Chinese Society of Clinical Oncology Guidelines, consisting of seven first-line and three second-line treatments. Five of these treatments were newly approved in China between 2021 and 2022. We evaluated the effectiveness and cost-effectiveness of these strategies from the Chinese healthcare system perspective. Methods: Network meta-analysis with non-proportional hazards was used to calculate the relative efficacy between interventions. A sequential model was developed to estimate costs and quality-adjusted life years (QALY) for treatment sequences with first-line platinum- and paclitaxel-based chemotherapy (SC) with or without nedaplatin, tislelizumab, camrelizumab, sintilimab, sugemalimab or pembrolizumab, followed by second-line docetaxel, tislelizumab or nivolumab. SC and docetaxel were used as comparators for first-line and second-line treatments, respectively. QALY and incremental cost-effectiveness ratio (ICER) were used to evaluate effectiveness and cost-effectiveness, respectively. Cost-effective threshold was set as USD 19,091. Subgroup analysis was conducted to determine the best first-line and second-line therapy. Results: Pembrolizumab + SC, followed by docetaxel (PED) was the most effective treatment sequence. QALYs for patients received SC, nedaplatin + SC, tislelizumab + SC, sintilimab + SC, camrelizumab + SC, sugemalimab + SC, pembrolizumab + SC followed by docetaxel were 0.866, 0.906, 1.179, 1.266, 1.179, 1.266, 1.603, 1.721, 1.807; QALYs for SC, nedaplatin + SC followed by tislelizumab were 1.283, 1.301; QALYs for SC, nedaplatin + SC followed by nivolumab were 1.353, 1.389. Camrelizumab + SC, followed by docetaxel (CAD) was the most cost-effective. Compared to SC with or without nedaplatin, tislelizumab, or sintilimab followed by docetaxel, ICERs of CAD were USD 12,276, 13,210, 6,974, 9,421/QALY, respectively. Compared with nedaplatin or SC followed by tislelizumab, the ICERs of CAD were USD 4,183, 2,804/QALY; CAD was dominant compared with nedaplatin or SC followed by nivolumab; The ICER of sugemalimab + SC followed by docetaxel and PED were USD 522,023, 481,639/QALY compared with CAD. Pembrolizumab + SC and camrelizumab + SC were the most effective and cost-effective first-line options, respectively; tislelizumab was the most effective and cost-effective second-line therapy. Tislelizumab used in second-line was more effective than first-line, no significant differences between their cost-effectiveness. Sensitivity and scenario analysis confirmed robustness of the results. Conclusions: PED and CAD are the most effective and cost-effective treatment sequence, respectively; pembrolizumab + SC and camrelizumab + SC are the most effective and cost-effective first-line choice, respectively; tislelizumab is the most effective and cost-effective second-line choice.

Estimating disease incidence rates and transition probabilities in elderly patients using multi-state models: a case study in fragility fracture using a Bayesian approach.

BACKGROUND: Multi-state models are complex stochastic models which focus on pathways defined by the temporal and sequential occurrence of numerous events of interest. In particular, the so-called illness-death models are especially useful for studying probabilities associated to diseases whose occurrence competes with other possible diseases, health conditions or death. They can be seen as a generalization of the competing risks models, which are widely used to estimate disease-incidences among populations with a high risk of death, such as elderly or cancer patients. The main advantage of the aforementioned illness-death models is that they allow the treatment of scenarios with non-terminal competing events that may occur sequentially, which competing risks models fail to do. METHODS: We propose an illness-death model using Cox proportional hazards models with Weibull baseline hazard functions, and applied the model to a study of recurrent hip fracture. Data came from the PREV2FO cohort and included 34491 patients aged 65 years and older who were discharged alive after a hospitalization due to an osteoporotic hip fracture between 2008-2015. We used a Bayesian approach to approximate the posterior distribution of each parameter of the model, and thus cumulative incidences and transition probabilities. We also compared these results with a competing risks specification. RESULTS: Posterior transition probabilities showed higher probabilities of death for men and increasing with age. Women were more likely to refracture as well as less likely to die after it. Free-event time was shown to reduce the probability of death. Estimations from the illness-death and the competing risks models were identical for those common transitions although the illness-death model provided additional information from the transition from refracture to death. CONCLUSIONS: We illustrated how multi-state models, in particular illness-death models, may be especially useful when dealing with survival scenarios which include multiple events, with competing diseases or when death is an unavoidable event to consider. Illness-death models via transition probabilities provide additional information of transitions from non-terminal health conditions to absorbing states such as death, what implies a deeper understanding of the real-world problem involved compared to competing risks models.

Trajetórias e determinantes do alto risco cardiovascular de 30 anos entre participantes de uma coorte brasileira (Estudo CUME) / Trajectories and determinants of 30-year high cardiovascular risk among participants in a Brazilian cohort (CUME Study)

Introdução: As doenças cardiovasculares são o principal problema de saúde pública em todo o mundo. Portanto, a avaliação do risco cardiovascular, com a identificação de seus fatores de risco e de proteção e de suas trajetórias ao longo do tempo são importantes para a proposição, a consolidação e a implementação de medidas de prevenção da ocorrência de doenças cardiovasculares. Objetivo geral: Analisar a trajetória e os determinantes do alto risco cardiovascular de 30 anos em participantes da Coorte de Universidades Mineiras (Estudo CUME). Métodos: Inicialmente, foi realizada uma revisão integrativa da literatura e, em seguida, dois estudos de coorte prospectiva. A) Artigo 1 ­ revisão integrativa da literatura sobre a estimação do alto risco cardiovascular e seus fatores associados, realizada nas bases Medical Literature Analysis and Retrievel System Online, Web of Science, Excerpta Medica Database, Cumulative Index to Nursing and Allied Health Literature e no portal Biblioteca Virtual de Saúde; B) Artigo 2 ­ Coorte aberta prospectiva desenvolvida com 2.854 participantes do Estudo CUME, que é uma pesquisa multicêntrica conduzida com egressos de sete instituições públicas federais de ensino superior do Estado de Minas Gerais desde 2016. A incidência do alto risco cardiovascular de 30 anos foi calculada usando o escore de Framingham e seus determinantes foram estimados usando análise multivariada hierárquica pela técnica de regressão de Cox; C) Artigo 3 ­ Estudo prospectivo fechado desenvolvido com 1.286 participantes da CUME, que responderam ao questionário da linha de base em 2016, aos questionários de seguimento de dois anos (2018) e de quatro anos (2020). O risco cardiovascular foi avaliado com o escore de Framingham de 30 anos. A identificação das trajetórias do risco cardiovascular foi realizada com a técnica de modelagem de crescimento de classe latente com o uso do modelo normal censurado. A análise dos fatores independentemente associados a cada uma das trajetórias foi conduzida com a técnica de regressão logística multinominal. Resultados: Artigo 1 ­ foram selecionados 13 artigos com um ou mais fatores associados ao alto risco cardiovascular, segundo o escore de Framingham de 10 anos. Nenhum artigo investigou os fatores associados ao alto risco cardiovascular de 30 anos. Artigo 2 ­ após média de 2,62 anos de seguimento, a incidência do alto risco cardiovascular de 30 anos foi 8,1 casos/1.000 pessoas-ano no sexo feminino e 20,2 casos/1.000 pessoas-ano no sexo masculino. Sexo masculino (Hazard Ratio ­ HR: 2,34; IC 95%: 1,58 - 3,46), trabalhar (HR: 2,13; IC 95%: 1,13 - 3,99), alto consumo de alimentos processados (HR: 2,44; 95% CI: 1,21 - 4,90) e ser ativo fisicamente (HR: 0,63; IC 95%: 0,41 - 0,98) se associaram independentemente ao alto risco cardiovascular de 30 anos; Artigo 3 - Três trajetórias de risco cardiovascular de 30 anos foram identificadas: Baixo-Baixo (68,3%), Médio-Médio (26,2%) e Alto-Alto (5,5%). Ao longo do tempo, o risco cardiovascular apresentou discreto aumento para a trajetória Baixo-Baixo (2,9%), moderado aumento para a trajetória Médio-Médio (7,6%) e elevado aumento para a trajetória Alto-Alto (13%). O sexo masculino, viver em união estável, ter consumos moderado e alto de alimentos ultraprocessados se associaram positivamente às trajetórias de risco cardiovascular Médio-Médio e Alto-Alto. Ainda, ter formação profissional fora da área da saúde e estar trabalhando se associaram positivamente à trajetória de risco cardiovascular Médio-Médio, enquanto ser ativo fisicamente se associou negativamente à trajetória de risco cardiovascular Alto-Alto. Conclusão: Poucos estudos foram conduzidos para avaliar o alto risco cardiovascular de 30 anos, sendo que em nenhum deles foram estimados fatores associados ao desfecho. Nossos achados científicos indicaram que praticar atividade física reduz a incidência do alto risco cardiovascular de 30 anos. Homens, pessoas que trabalham e com consumo elevado de alimentos processados devem ser monitorados com maior cautela, pois apresentaram maior susceptibilidade de ocorrência do alto risco cardiovascular de 30 anos. Adultos jovens e com melhor situação socioeconômica possuem uma trajetória de baixo risco cardiovascular de 30 anos, entretanto, há uma tendência de piora desta trajetória ao longo do tempo devido aos maus hábitos de vida. Dessa forma, é essencial a implementação de estratégias de prevenção para evitar o adoecimento cardiovascular.

Introduction: Cardiovascular diseases are the main public health problem worldwide. Therefore, the assessment of cardiovascular risk, with the identification of its risk and protection factors and their trajectories over time, are important for proposing, consolidating and implementing measures to prevent the occurrence of cardiovascular diseases. General objective: To analyze the 30-year trajectory and determinants of high cardiovascular risk in participants of the Cohort of Universities of Minas Gerais (CUME Study). Methods: Initially, an integrative literature review was performed, followed by two prospective cohort studies. A) Article 1 ­ integrative review of the literature on the estimation of high cardiovascular risk and its associated factors, carried out in the databases Medical Literature Analysis and Retrievel System Online, Web of Science, Excerpta Medica Database, Cumulative Index to Nursing and Allied Health Literature and the Virtual Health Library portal; B) Article 2 ­ Prospective open cohort developed with 2,854 participants of the CUME Study, which is a multicenter research conducted with graduates from seven federal public institutions of higher education in the State of Minas Gerais since 2016. The incidence of high cardiovascular risk at 30 years was calculated using the Framingham score and its determinants were estimated using hierarchical multivariate analysis by the Cox regression technique; C) Article 3 ­ Prospective closed study developed with 1,286 participants from CUME, who answered the baseline questionnaire in 2016, the two-year follow-up questionnaire in 2018 and the four-year follow-up questionnaire in 2020. The risk Cardiovascular was assessed using the 30-year Framingham score. The identification of cardiovascular risk trajectories was performed using the latent class growth modeling technique using the normal censored model. The analysis of the factors independently associated with each of the trajectories was conducted using the multinomial logistic regression technique. Results: Article 1 ­ 13 articles were selected with one or more factors associated with high cardiovascular risk, according to the Framingham score over 10 years. No article investigated the factors associated with 30-year high cardiovascular risk. Article 2 ­ After an average of 2.62 years of follow-up, the incidence of high cardiovascular risk at 30 years was 8.1 cases/1,000 person-years in females and 20.2 cases/1,000 person-years in males. Male sex (Hazard Ratio ­ HR: 2.34; 95% CI: 1.58 - 3.46), work (HR: 2.13; 95% CI: 1.13 - 3.99), high food intake processed foods (HR: 2.44; 95% CI: 1.21 - 4.90) and being physically active (HR: 0.63; 95% CI: 0.41 - 0.98) were independently associated with high cardiovascular risk 30 years old; Article 3 - Three 30-year cardiovascular risk trajectories were identified: Low-Low (68.3%), Medium-Medium (26.2%) and High-High (5.5%). Over time, cardiovascular risk showed a slight increase for the Low-Low trajectory (2.9%), a moderate increase for the Medium-Medium trajectory (7.6%) and a high increase for the High-High trajectory (13%). Being male, living in a stable relationship, having moderate and high consumption of ultra-processed foods were positively associated with Medium-Medium and High-High cardiovascular risk trajectories. Also, having professional training outside the health area and being working were positively associated with the Medium-Medium cardiovascular risk trajectory, while being physically active was negatively associated with the High-High cardiovascular risk trajectory. Conclusion: Few studies were conducted to assess the 30-year high cardiovascular risk, and none of them estimated factors associated with the outcome. Our scientific findings indicated that practicing physical activity reduces the incidence of 30-year high cardiovascular risk. Men, people who work and with a high consumption of processed foods should be monitored with greater caution, as they were more susceptible to the occurrence of the high cardiovascular risk of 30 years. Young adults with better socioeconomic status have a 30-year trajectory of low cardiovascular risk, however, there is a tendency for this trajectory to worsen over time due to bad lifestyle habits. Thus, it is essential to implement prevention strategies to avoid cardiovascular disease.

Identifying optimal PD-1/PD-L1 inhibitors in first-line treatment of patients with advanced squamous non-small cell lung cancer in China: Updated systematic review and network meta-analysis.

Objective: After Gemstone-302 was published in Lancet in January 2022, seven PD-(L)1 inhibitors launched or about to be launched in China, but there are no head-to-head RCTs reporting the comparative efficacy for squamous non-small cell lung cancer (sq-NSCLC). Therefore, we aimed to indirectly compare the efficacy of these treatments to provide evidence for clinical decision and Chinese national reimbursement drug listing. Methods: We collected phase III clinical trials targeted on stage IIIB-IV patients for first-line immunotherapy of sq-NSCLC by systematically searching databases. Relative effects of competing treatments were assessed by Bayesian network meta-analysis and non-parametric restricted mean survival time (RMST) model. Hazard ratio (HR), severe adverse events (SAEs, grade 3-5), progression-free survival (PFS) and overall survival (OS) years were the outcomes. Subgroup analysis was done according to PD-(L)1 expression, smoking, gender, Eastern Cooperative Oncology Group performance status, age and disease stage. Sensitivity analysis using the range of parameters distribution as well as different comparison methods was performed to test the robustness of the results. Results: A total of 7 clinical trials with 2,640 patients were included. For OS, the efficiency (HR, 95%CI) ranks from high to low were sugemalimab (0.48, 0.32-0.73), camrelizumab (0.55, 0.40-0.76), sintilimab (0.56, 0.35-0.90), pembrolizumab (0.71, 0.58-0.87) and atezolizumab (0.88, 0.73-1.05). For PFS, the efficiency ranks from high to low were sugemalimab (0.33, 0.24-0.45), camrelizumab (0.37, 0.30-0.46), tislelizumab (0.53, 0.36-0.79), sintilimab (0.54, 0.42-0.69), toripalimab (0.56, 0.38-0.83), pembrolizumab (0.57, 0.47-0.70) and atezolizumab (0.71, 0.59-0.85). Proportional hazard models and non-proportional hazard models showed consistent efficiency ranks. When extrapolated to long-term survival benefit, under non-proportional hazard ratio, sugemalimab achieved the highest PFS benefit (lifeyears, LYs) in 2 years (1.323), with camrelizumab (1.320), sintilimab (1.243), tislelizumab (1.189), pembrolizumab (0.990) and atezolizumab (0.947) ranking in order; Camrelizumab achieved the highest OS benefit (LYs) in 10 years (2.723), with atezolizumab (2.445) and pembrolizumab (2.397) ranking in order. RMST model showed similar results. In terms of safety, PD-(L)1 inhibitors increased the incidence of SAEs when combined with chemotherapy, sugemalimab and camrelizumab was the safest drugs. Conclusion: Sugemalimab is superior both in HR and long-term survival benefit for Chinese patients with advanced sq-NSCLC.

The interplay of race/ethnicity and education in fertility patterns.

This study examines the interplay between race/ethnicity and educational attainment in shaping completed fertility in the United States for women born 1961-80. Using data from the National Survey of Family Growth, 2006-17, we apply multilevel, multiprocess hazard models to account for unobserved heterogeneity and to estimate (1) cohort total fertility rates, (2) parity progression ratios, and (3) parity-specific fertility timing, for non-Hispanic white, non-Hispanic Black, and Hispanic women by educational attainment. We find that compared with their white counterparts, fertility was higher among Black and Hispanic women with less than high school education. However, among college-educated women, fertility levels were lowest among Black women and highest among Hispanic women. The difference in fertility between college-educated Black and white women is driven mainly by the smaller proportion of Black mothers having second births. We find little evidence that the observed racial/ethnic disparities in fertility levels by educational attainment are driven by differences in fertility timing.

Machine learning prediction of atrial fibrillation in cardiovascular patients using cardiac magnetic resonance and electronic health information.

Background: Atrial fibrillation (AF) is a commonly encountered cardiac arrhythmia associated with morbidity and substantial healthcare costs. While patients with cardiovascular disease experience the greatest risk of new-onset AF, no risk model has been developed to predict AF occurrence in this population. We hypothesized that a patient-specific model could be delivered using cardiovascular magnetic resonance (CMR) disease phenotyping, contextual patient health information, and machine learning. Methods: Nine thousand four hundred forty-eight patients referred for CMR imaging were enrolled and followed over a 5-year period. Seven thousand, six hundred thirty-nine had no prior history of AF and were eligible to train and validate machine learning algorithms. Random survival forests (RSFs) were used to predict new-onset AF and compared to Cox proportional-hazard (CPH) models. The best performing features were identified from 115 variables sourced from three data domains: (i) CMR-based disease phenotype, (ii) patient health questionnaire, and (iii) electronic health records. We evaluated discriminative performance of optimized models using C-index and time-dependent AUC (tAUC). Results: A RSF-based model of 20 variables (CIROC-AF-20) delivered an overall C-index of 0.78 for the prediction of new-onset AF with respective tAUCs of 0.80, 0.79, and 0.78 at 1-, 2- and 3-years. This outperformed a novel CPH-based model and historic AF risk scores. At 1-year of follow-up, validation cohort patients classified as high-risk of future AF by CIROC-AF-20 went on to experience a 17.3% incidence of new-onset AF, being 24.7-fold higher risk than low risk patients. Conclusions: Using phenotypic data available at time of CMR imaging we developed and validated the first described risk model for the prediction of new-onset AF in patients with cardiovascular disease. Complementary value was provided by variables from patient-reported measures of health and the electronic health record, illustrating the value of multi-domain phenotypic data for the prediction of AF.

La albuminuria y la enfermedad polivascular mejoran la capacidad predictiva de los modelos multivariados después de un evento cardiovascular agudo. Cohorte AIRVAG / Albuminuria and polyvascular disease improve multivariate predictive models after an acute cardiovascular event. The AIRVAG cohort

Antecedentes y objetivos: En la enfermedad cardiovascular ateroesclerótica no existe consenso respecto a los instrumentos de estratificación del riesgo en su prevención secundaria. Nuestro objetivo consistía en comparar la capacidad discriminativa de las funciones de riesgo de Framingham, REGICOR, SCORE y REACH y las puntuaciones de riesgo Bohula-TIMI y SMART, así como en evaluar el posible valor añadido de otras variables clínicas en cuanto a la predicción de recurrencias en pacientes con enfermedad cardiovascular. Métodos: Se analizó una cohorte de 269 pacientes con enfermedad cardiovascular establecida (52,8% coronaria, 32% cerebrovascular, 15,2% arteriopatía periférica). Se compararon las funciones de supervivencia de los grupos de riesgo (bajo/intermedio/alto) según los valores de corte de uso habitual de cada función o puntuación y se calcularon las razones de riesgos instantáneos (RRI) correspondientes a cada una mediante regresión de Cox. Se calculó el Δ C de Harrell, el cat-IRN y el cIRN después de añadir nuevos factores predictivos a un modelo base que incluía edad, sexo, colesterol total, tabaquismo activo, hipertensión arterial y diabetes. Resultados: Al cabo de 6 años de seguimiento (mediana de 4,82 años) se habían producido 61 eventos (23%). Los grupos de riesgo alto tuvieron un mayor riesgo de recurrencia: SMART (RRI: 3,17 [1,55-6,5]), Framingham (RRI: 3,08 [1,65-5,75]), REGICOR (RRI: 2,71 [1,39-5,27]), SCORE (RRI: 2,14 [1,01-4,5], REACH (RRI: 5,74 [2,83-11,7]) y B-TIMI (RRI: 3,68 [0,88-15,3]). La enfermedad polivascular (3 territorios, RRI: 5,6 [2,2-14,25]), la albuminuria (RRI: 3,55 [2,06-6,11]) y la insuficiencia cardíaca (RRI: 3,11 [1,34-7,25]) también incrementaron el riesgo. La capacidad discriminativa (índice C de Harrell) fue baja, pero mejoró tras añadir la albuminuria y la enfermedad polivascular. Ambas variables también mejoraron el rendimiento del modelo base (cIRN: 0,326 [0,036; 0,607]) (AU)

Background and aims: There is no consensus regarding risk stratification tools for secondary prevention in atherosclerotic cardiovascular disease. Our aim was to compare the discriminative performance of the Framingham, REGICOR, SCORE, and REACH risk functions and the Bohula-TIMI and SMART risk scores, as well as to assess the potential added value of other clinical variables for the prediction of recurrent events in patients with established vascular disease. Methods: A cohort of 269 patients with established vascular disease (52.8% coronary, 32% cerebrovascular, 15.2% peripheral artery disease) was included. The survival functions of risk groups (low/medium/high) according to commonly used cutoff points for each function/score were compared, and hazard ratios (HR) for each were estimated using Cox regression. We calculated Δ Harrell's C statistic, cat-NRI, and cNRI after adding new predictors to a base model including age, sex, total cholesterol, current smoking status, hypertension, and diabetes. Results: After 6 years of follow-up (median 4.82 years), 61 events occurred (23%). High-risk groups had a higher risk of recurrent event: SMART (HR: 3.17 [1.55-6.5]), Framingham (HR: 3.08 [1.65-5.75]), REGICOR (HR: 2.71 [1.39-5.27]), SCORE (HR: 2.14 [1.01-4.5], REACH (HR: 5.74 [2.83-11.7]), B-TIMI (HR: 3.68 [0.88-15.3]). Polyvascular disease (3 territories HR: 5.6 [2.2-14.25]), albuminuria (HR: 3.55 [2.06-6.11]), and heart failure (HR: 3.11 [1.34-7.25]) also increased risk. Discrimination (Harrell's C) was low but improved after adding albuminuria and polyvascular disease. Both variables also improved the performance of the base model (cNRI: 0.326 [0.036; 0.607]). Conclusions: The Framingham, REGICOR, SCORE, and REACH functions and the B-TIMI and SMART scores showed low yet similar performance in secondary prevention. Albuminuria and polyvascular disease improved the predictive performance of major classical cardiovascular risk factors (AU)

The impact of frailty on mortality in non-surgical head and neck cancer treatment: Shifting the clinical paradigm.

OBJECTIVE: Compare survival of head and neck cancer (HNC) patients treated with surgical or non-surgical management according to frailty, quantify frailty with the Risk Analysis Index (RAI), a validated 14-item instrument. MATERIALS AND METHODS: Prospective cohort study of newly diagnosed HNC patients (≥18 years) who had frailty assessment from April 13, 2016 to September 30, 2016. Primary outcome was overall survival at 1- and 3-years. Cox proportional hazard models were utilized to examine mortality with predictor variables. Adjusted and unadjusted (Kaplan-Meier) survival curves stratified by either RAI scores or treatment modality were plotted. Kruskal-Wallis and likelihood ratio chi-square tests were used for comparing clinicodemographic variables. RESULTS: Of 165 patients, 54 (32.7%) were managed non-surgically, 49 (29.7%) were treated with definitive surgery only, and 62 (37.6%) were treated with multimodality (surgery + adjuvant) therapy. Among the full cohort and subgroup analysis of the frail/very frail (RAI ≥ 37), non-surgical patients had worse or similar 3-year survival than those treated with surgery +/- adjuvant therapy. Multivariable Cox proportional hazard models demonstrate that frail patients treated non-surgically experienced worse survival than their counterparts treated with surgery (HR = 2.50, p = 0.015, 95% CI: 1.19, 5.23) or multimodality therapy (HR = 3.91, p < 0.001, 95% CI: 1.94-7.89). CONCLUSION: Across all levels of frailty, long term survival of HNC patients treated without surgery is either worse than or like those treated with surgery. These findings (1) challenge current practices of steering patients "too frail for surgery" towards non-surgical, "non-invasive" therapy, and (2) suggest equipoise warranting randomized trials to clarify treatment of frail patients.

Albuminuria and polyvascular disease improve multivariate predictive models after an acute cardiovascular event. The AIRVAG cohort.

BACKGROUND AND AIMS: There is no consensus regarding risk stratification tools for secondary prevention in atherosclerotic cardiovascular disease. Our aim was to compare the discriminative performance of the Framingham, REGICOR, SCORE, and REACH risk functions and the Bohula-TIMI and SMART risk scores, as well as to assess the potential added value of other clinical variables for the prediction of recurrent events in patients with established vascular disease. METHODS: A cohort of 269 patients with established vascular disease (52.8% coronary, 32% cerebrovascular, 15.2% PAD) was included. The survival functions of risk groups (low/medium/high) according to commonly used cutoff points for each function/score were compared, and hazard ratios for each were estimated using Cox regression. We calculated Δ Harrell's C statistic, cat-NRI, and cNRI after adding new predictors to a base model including age, sex, total cholesterol, current smoking status, hypertension, and diabetes. RESULTS: After six years of follow-up (median 4.82 years), 61 events occurred (23%). High-risk groups had a higher risk of recurrent event: SMART (HR: 3.17 [1.55-6.5]), Framingham (HR: 3.08 [1.65-5.75]), REGICOR (HR: 2.71 [1.39-5.27]), SCORE (HR: 2.14 [1.01-4.5], REACH (HR: 5.74 [2.83-11.7]), B-TIMI (HR: 3.68 [0.88-15.3]). Polyvascular disease (three territories HR: 5.6 [2.2-14.25]), albuminuria (HR: 3.55 [2.06-6.11]), and heart failure (HR: 3.11 [1.34-7.25]) also increased risk. Discrimination (Harrell's C) was low but improved after adding albuminuria and polyvascular disease. Both variables also improved the performance of the base model (cNRI.326 [.036; .607]). CONCLUSIONS: The Framingham, REGICOR, SCORE, and REACH functions and the B-TIMI and SMART scores showed low yet similar performance in secondary prevention. Albuminuria and polyvascular disease improved the predictive performance of major classical cardiovascular risk factors.

How Does Diet Influence Our Lives? Evaluating the Relationship between Isotopic Signatures and Mortality Patterns in Italian Roman Imperial and Medieval Periods.

The present research investigates the relationship between dietary habits and mortality patterns in the Roman Imperial and Medieval periods. The reconstructions of population dynamics and subsistence strategies provide a fascinating source of information for understanding our history. This is particularly true given that the changes in social, economic, political, and religious aspects related to the transition from the Roman period to the Middle Ages have been widely discussed. We analyzed the isotopic and mortality patterns of 616 individuals from 18 archeological sites (the Medieval Latium sites of Colonna, Santa Severa, Allumiere, Cencelle, and 14 Medieval and Imperial funerary contexts from Rome) to compile a survivorship analysis. A semi-parametric approach was applied, suggesting variations in mortality patterns between sexes in the Roman period. Nitrogen isotopic signatures influenced mortality in both periods, showing a quadratic and a linear effect for Roman Imperial and Medieval populations, respectively. No influence of carbon isotopic signatures has been detected for Roman Imperial populations. Conversely, increased mortality risk for rising carbon isotopic values was observed in Medieval samples.

Periodontitis as a Risk Factor for Rheumatoid Arthritis: a Matched-Cohort Study.

OBJECTIVE: The intent was to analyse the association of periodontitis with the development of rheumatoid arthritis (RA) using a representative population-based cohort and longitudinal matched-cohort design. METHODS: Participants were 40 years of age or older and had not been diagnosed with RA between 2002 and 2006. Among the participants, those who were newly diagnosed with periodontitis between 2004 and 2006 (excluding cases that had already been diagnosed with periodontitis between 2002 and 2003) were allotted to the periodontitis group. Among the participants, those who had never been diagnosed with periodontitis between 2002 and 2006 formed the control group, matched by sex, age, and household income at a 1:1 ratio. From 2007 to 2018, the 2 groups (n = 691,506) were followed to monitor the development of RA. The t-test and χ2 test compared the general characteristics and health-related variables of both groups. The Kaplan-Meier method with a log-rank test was conducted to compare the incidence of RA in both groups. The hazard ratio (HR) and adjusted hazard ratio (aHR) were calculated using a Cox proportional hazard regression analysis to evaluate the risk of subsequent RA. RESULTS: Univariate analysis revealed that the periodontitis group was more likely to develop RA than the control group (hazard ratio 1.10), and multivariate analysis also revealed a higher incidence risk of RA (adjusted hazard ratio 1.09) in the periodontitis group. CONCLUSIONS: Our findings demonstrate that periodontitis is associated with an increased risk of developing RA.