Multistate Approach Research Articles

Joint analysis of duration of ventilation, length of intensive care, and mortality of COVID-19 patients: a multistate approach

BackgroundThe clinical progress of patients hospitalized due to COVID-19 is often associated with severe pneumonia which may require intensive care, invasive ventilation, or extracorporeal membrane oxygenation (ECMO). The length of intensive care and the duration of these supportive therapies are clinically relevant outcomes. From the statistical perspective, these quantities are challenging to estimate due to episodes being time-dependent and potentially multiple, as well as being determined by the competing, terminal events of discharge alive and death.MethodsWe used multistate models to study COVID-19 patients’ time-dependent progress and provide a statistical framework to estimate hazard rates and transition probabilities. These estimates can then be used to quantify average sojourn times of clinically important states such as intensive care and invasive ventilation. We have made two real data sets of COVID-19 patients (n = 24* and n = 53**) and the corresponding statistical code publically available.ResultsThe expected lengths of intensive care unit (ICU) stay at day 28 for the two cohorts were 15.05* and 19.62** days, while expected durations of mechanical ventilation were 7.97* and 9.85** days. Predicted mortality stood at 51%* and 15%**. Patients mechanically ventilated at the start of the example studies had a longer expected duration of ventilation (12.25*, 14.57** days) compared to patients non-ventilated (4.34*, 1.41** days) after 28 days. Furthermore, initially ventilated patients had a higher risk of death (54%* and 20%** vs. 48%* and 6%**) after 4 weeks. These results are further illustrated in stacked probability plots for the two groups from time zero, as well as for the entire cohort which depicts the predicted proportions of the patients in each state over follow-up.ConclusionsThe multistate approach gives important insights into the progress of COVID-19 patients in terms of ventilation duration, length of ICU stay, and mortality. In addition to avoiding frequent pitfalls in survival analysis, the methodology enables active cases to be analyzed by allowing for censoring. The stacked probability plots provide extensive information in a concise manner that can be easily conveyed to decision makers regarding healthcare capacities. Furthermore, clear comparisons can be made among different baseline characteristics.

A comparison of partitioned survival analysis and state transition multi-state modelling approaches using a case study in oncology

Aims To construct and compare a partitioned-survival analysis (PartSA) and a semi-Markov multi-state model (MSM) to investigate differences in estimated cost effectiveness of a novel cancer treatment from a UK perspective. Materials and Methods Data from a cohort of late-stage cancer patients (N > 700) enrolled within a randomized, controlled trial were used to populate both modelling approaches. The statistical software R was used to fit parametric survival models to overall survival (OS) and progression-free survival (PFS) data to inform the PartSA (package “flexsurv”). The package “mstate” was used to estimate the MSM transitions (permitted transitions: (T1) “progression-free” to “dead”, (T2) “post-progression” to “death”, and (T3) “pre-progression” to “post-progression”). Key costs included were treatment-related (initial, subsequent, and concomitant), adverse events, hospitalizations and monitoring. Utilities were stratified by progression. Outcomes were discounted at 3.5% per annum over a 15-year time horizon. Results The PartSA and MSM approaches estimated incremental cost-effectiveness ratios (ICERs) of £342,474 and £411,574, respectively. Scenario analyses exploring alternative parametric forms provided incremental discounted life-year estimates that ranged from +0.15 to +0.33 for the PartSA approach, compared with −0.13 to +0.23 for the MSM approach. This variation was reflected in the range of ICERs. The PartSA produced ICERs between £234,829 and £522,963, whereas MSM results were more variable and included instances where the intervention was dominated and ICERs above £7 million (caused by very small incremental QALYs). Limitations and conclusions Structural uncertainty in economic modelling is rarely explored due to time and resource limitations. This comparison of structural approaches indicates that the choice of structure may have a profound impact on cost-effectiveness results. This highlights the importance of carefully considered model conceptualization, and the need for further research to ascertain when it may be most appropriate to use each approach.

A study on the factors affecting household solar adoption in Kerala, India

PurposeRecent research on the energy system highlights the need for understanding the bandwidth of drivers and inhibitors of household investor's behaviour in rooftop PV (or photovoltaic power system) and to fit the broader socio-economic context in which they are deployed. However, apart from few exceptions, these newer perspectives have not been duly applied in the research on rooftop PV. This paper aims to fill this gap and to shed new light on rooftop PV investment decisions.Design/methodology/approachThis study has been conducted with the primary data collected using two data sets of 237 households and 387 households of Indian southern state Kerala using survey-based questionnaire. The findings from first data set revealed that households considering the adoption of PV were likely influenced by six distinct factors, three motivators and three inhibitors. Second data set for multi-state analytic approach was proposed whereby the research model was tested using structural equation modelling (SEM). The outcomes of SEM were used as inputs for an artificial neural network (ANN) model for forecasting investor investment decision in in renewables. The ANN model was also used to rank the relative influence of significant predictors obtained from SEM.FindingsIn line with the risk–return framework, government subsidies act as primary motivator which helps in overcoming the initial risk of investment in the new technology. Further, low prices and low cost of maintenance are some of the financial motivators which may likely mitigate the long-term apprehension of returns and maintenance cost. Lastly, the strongest motivators of PV investment come from the environmental and financial motivator in the form of PV subsidies, which further solidifies the role of policy interventions in investment decision. The ANN model identified the technical barrier and knowledge and awareness factors play a significant role in forcasting the investor investing decision.Practical implicationsThe study results will be useful for policymakers for framing strategies to attract and influence their investment in renewable energy.Originality/valueBuilding upon behavioural finance and institutional theory, this paper posits that, in addition to a rational evaluation of the economics of the investment opportunities, various non-financial factors affect the household's decision to invest in renewables.

A Multi-State Approach to Modelling Intermediate Events and Multiple Mortgage Loan Outcomes

This paper proposes a novel system-wide multi-state framework to model state occupations and the transitions among current, delinquency, default, prepayment, repurchase, short sale and foreclosure on mortgage loans. The approach allows for the modelling of the progression of borrowers from one state to another to fully understand the risks of a cohort of borrowers over time. We use a multi-state Markov model to model the transitions to and from various states. The key factors affecting the transition into various loan outcomes are the ability to pay as measured by debt-to-income ratio, equity as marked by loan-to-value ratio, interest rates and the property type. Our findings have broader policy implications for better decision-making on granting loans and the design of debt relief and mortgage modification policies.

Using a multistate occupancy approach to determine molecular diagnostic accuracy and factors affecting avian haemosporidian infections

The use of a sensitive and accurate parasite detection methodology is crucial in studies exploring prevalence of parasites in host populations or communities, and uncertainty in identifying parasite genera and/or lineages may limit the understanding of host-parasite interactions. Here, we used a multistate occupancy approach that accounts for imperfect detection to assess whether sex and breeding season influenced the prevalence of a specific Haemoproteus lineage (TARUF02) in a white-lined tanager population. Likewise, we explored whether the probability of detecting the target parasite in an infected bird using PCR and sequencing analyses may be influenced by season and host sex. We found little evidence that sex influenced the probability of an individual host being infected by a haemosporidian parasite. Conversely, we found that the probability of infection by Haemoproteus TARUF02 was ~30% higher during the breeding season, reflecting a higher prevalence of this parasite in this season. The probability that PCR detects DNA of haemosporidian parasite was higher for female birds, suggesting that they are more prone to be parasitized with parasitemia levels that are more successfully detected by molecular analysis. Sequencing successfully determined the Haemoproteus TARUF02 lineage in 60% of samples collected during the breeding season and 84% of samples collected during the non-breeding season. Understanding the ecology of hosts and aspects of their physiology that may influence the parasite infection is essential to better understanding of hemoparasite infections and how parasites influence their native hosts, through decreasing reproductive success, lifespan, and/or survival.

Modeling Viral Suppression, Viral Rebound and State-Specific Duration of HIV Patients with CD4 Count Adjustment: Parametric Multistate Frailty Model Approach.

IntroductionCombination antiretroviral therapy has become the standard care of human immunodeficiency virus (HIV)-infected patients and has further led to a dramatically decreased progression probability to acquired immune deficiency syndrome (AIDS) for patients under such a therapy. However, responses of the patients to this therapy have recorded heterogeneous complexity and high dynamism. In this paper, we simultaneously model long-term viral suppression, viral rebound, and state-specific duration of HIV-infected patients.MethodsFull-parametric and semi-parametric Markov multistate models were applied to assess the effects of covariates namely TB co-infection, educational status, marital status, age, quality of life (QoL) scores, white and red blood cell parameters, and liver enzyme abnormality on long-term viral suppression, viral rebound and state-specific duration for HIV-infected individuals before and after treatment. Furthermore, two models, one including and another excluding the effect of the frailty, were presented and compared in this study.ResultsResults from the diagnostic plots, Akaike information criterion (AIC) and likelihood ratio test showed that the Weibull multistate frailty model fitted significantly better than the exponential and semi-parametric multistate models. Viral rebound was found to be significantly associated with many sex partners, higher eosinophils count, younger age, lower educational level, higher monocyte counts, having abnormal neutrophils count, and higher liver enzyme abnormality. Furthermore, viral suppression was also found to be significantly associated with higher QoL scores, and having a stable sex partner. The analysis result also showed that patients with a stable sex partner, higher educational levels, higher QoL scores, lower eosinophils count, lower monocyte counts, and higher RBC indices were more likely to spend more time in undetectable viral load state.ConclusionsTo achieve and maintain the UNAIDS 90% suppression targets, additional interventions are required to optimize antiretroviral therapy outcomes, specifically targeting those with poor clinical characteristics, lower education, younger age, and those with many sex partners. From a methodological perspective, the parametric multistate approach with frailty is a flexible approach for modeling time-varying variables, allowing for dealing with heterogeneity between the sequence of transitions, as well as allowing for a reasonable degree of flexibility with a few additional parameters, which then aids in gaining a better insight into how factors change over time.

A multi-state model analysis of the time from ethical approval to publication of clinical research studies.

BackgroundResults of medical research should be made publicly available in a timely manner to enable patients and health professionals to make informed decisions about health issues. We aimed to apply a multi-state model to analyze the overall time needed to publish study results, and to examine predictors of the timing of transitions within the research process from study initiation through completion/discontinuation to eventual publication.MethodsUsing a newly developed multi-state model approach, we analysed the effect of different study-related factors on each of the transitions from study approval to eventual publication, using a data set of clinical studies approved by a German research ethics committee between 2000 and 2002.ResultsOf 917 approved studies, 806 were included in our analyses. About half of the clinical studies which began were subsequently published as full articles, and the median time from study approval to publication was 10 years. Differences across model states were apparent; several factors were predictive of the transition from study approval to completion, while funding source and collaboration were predictive of the transition from completion to publication.ConclusionsThe proposed multi-state model approach permits a more comprehensive analysis of time to publication than a simple examination of the transition from approval to publication, and thus the findings represent an advance on previous studies of this aspect of the research process.

Evaluating self reported student competency in clinically integrated histopathology using a multi-station based and student-centred approach in graduate medical education

Aim: To develop and evaluate a pathology curriculum which has substituted didactic practicals for a multi-station tutorial integrating self-assessment questions, clinical scenarios and pathology. Method: Eighty medical students were asked to review the curriculum using qualitative comments and based on a quantitative Likert scale. Results: We demonstrated that the multi-station approach improved student understanding of anatomy, histology, radiology, macroscopic pathology and clinical practice. There was improvement of student self-reported understanding of the clinical applications of pathology (2.19±0.1 in old curriculum versus 3.25±0.09 in new curriculum, p<0.05). In addition, we showed that this new teaching approach integrated well with the problem-based learning and provided students with more autonomy to approach their learning in ways that worked for them (2.13±0.12 old versus 2.67±0.12 new, p<0.05). Finally, the students regarded the self-assessment questions being the most useful (3.80±0.05), followed by the presence of student tutors (3.65±0.62). Discussion: Engaging the medical students to study clinically integrated histopathology using a multi-station based and student-centred approach is highly useful for learning of pathology in problem-based learning settings.

Improvement of Ab Initio Ligand Field Theory by Means of Multistate Perturbation Theory.

Over the last few years, ab initio ligand field theory (AILFT) has evolved into an important tool for the extraction of ligand field models from ab initio calculations. The inclusion of dynamic correlation on top of complete active space self-consistent field (CASSCF) reference functions, which is important for accurate results, was so far realized at the level of second-order N-electron valence state perturbation theory (NEVPT2). In this work, we introduce two alternative methods for the inclusion of dynamic correlation into AILFT calculations, the second-order dynamic correlation dressed complete active space method (DCD-CAS(2)) and the Hermitian quasi-degenerate NEVPT2 (HQD-NEVPT2). These methods belong to the class of multistate perturbation theory approaches, which allow for the mixing of CASSCF states under the effect of dynamic correlation (state-mixing). The two new versions of AILFT were tested for a diverse set of transition-metal complexes. It was found that the multistate methods have, compared to NEVPT2, an AILFT fit with smaller root mean square deviations (rmsds) between ab initio and AILFT energies. A comparison of AILFT excitation energies with the experiment shows that for some systems, the agreement gets better at the multistate level because of the smaller rmsds. However, for some systems, the agreement gets worse, which could be attributed to a cancellation of errors at the NEVPT2 level that is partly removed at the multistate level. An investigation of trends in the extracted ligand field parameters shows that at the multistate level, the ligand field splitting Δ gets larger, whereas the Racah parameters B and C get smaller and larger, respectively. An investigation of the reasons for the observed improvement for octahedral CrIII halide complexes shows that the possibility of state-mixing relaxes constraints that are present at the NEVPT2 level and that keep Δ and B from following their individual preferences.

Neuropsychiatric events in systemic lupus erythematosus: a longitudinal analysis of outcomes in an international inception cohort using a multistate model approach

ObjectivesUsing a reversible multistate model, we prospectively examined neuropsychiatric (NP) events for attribution, outcome and association with health-related quality of life (HRQoL), in an international, inception cohort of systemic lupus...

Supply chain multi-state risk assessment using universal generating function

This paper proposes a new approach to assess the supply risk beyond the classical binary assumption of either delivering the whole quantity or not. Given today’s stochastic nature of supply and the dynamic nature of demand, the different supply activities along with the chain exhibit a multi-state behaviour increasing the complexity of their risk assessment. The new approach utilizes the universal generating function (UGF) to model the different suppliers’ echelons with their various supply risk levels along all the stages of the supply chain as a multi-state risk system. The developed model was successfully implemented to assess the supply risk in a multi-state strawberry supply chain and outperformed classical approaches. Results from the case study and the validation analysis illustrated the ability of the new approach to capture the various supply levels with their associated risks leading to more informative risk assessment process. Furthermore, the developed model improved the visibility for the purchasing managers downstream in terms of the different trade-offs between supply levels and their risks as well as some financial thresholds. The new multi-state approach contributes to the emerging supply chain risk assessment trend by offering a more realistic modelling method to capture the risk of all available supply levels along the delivery chain.

A multi-state model based reanalysis of the Framingham Heart Study: Is dementia incidence really declining?

Recent research by Satizabal and colleagues using data from the Framingham Heart Study demonstrated a linear decline in dementia incidence since the 1970s. The aim of this study is to re-examine these findings, given concerns that bias resulted from failure to account for the probability of acquiring dementia between the last dementia-free observation and death. This analysis included 5118 persons 60+ years of age, and determined the 5-year dementia incidence during four non-overlapping epochs. In addition to a replication using Cox proportional hazards, we applied separate Cox models (given unequal hazards across epochs) and a Spline-based penalized likelihood approach based on the illness-death multi-state model. In addition, we present a simulation study demonstrating the bias associated with the use of standard survival models. The simulation showed that estimates of disease incidence derived from the multi-state model-based approach were consistent with the true disease incidence, whereas Cox regression 'censoring' observations at death or at last observationconsistently underestimated it. Using the Framingham data, the 5-year age- and sex-adjusted cumulative hazard rates for dementia as derived from the multi-state model-based approach were 3.84, 2.66, 3.29 and 3.13 per 100 persons in epochs 1, 2, 3 and 4 respectively. The findings do not support the conclusion that dementia incidence has declined in the Framingham Heart Study over the given time period. Previous findings of a decline may have been an artefact resulting from improper treatment of those cases in which death precluded the observation of dementia onset.

Inequalities in Life Expectancy With Frailty Among Brazilian Older Adults: A Multistate Approach

Background and ObjectivesFrailty is considered one of the major conditions faced by aging societies. Little has been reported about the effect of becoming frail on life expectancy among older adults in developing countries. The aim was to estimate total life expectancy and life expectancy with or without frailty by age, sex, and education among older adults in Brazil.Data and Methods: The study was developed based on information provided by the Health, Well-being, and Aging (SABE) Study. The sample included 1,399 older adults (≥60 years old) followed up from 2006 to 2010. Frailty status was classified according to the Fried criteria. Additional variables include age (in years), gender, and years of education. Estimates of total life expectancy, frailty-free life expectancy, and frailty life expectancy were obtained using the multistate life table method.ResultsAt the baseline, the proportion of individuals with frailty was 13.7% and participants had, on average, 4.0 years of education. Men had more years of education than women (4.6 vs. 3.7, p < .001). Older adults with higher education live fewer years with frailty. Compared with older adults with no education, those with 6 years of education have higher frailty-free life expectancy. At age 70, men with no education expect to live 9.1 years (95% confidence interval [CI] = 7.8, 10.4) without frailty compared with 10.6 years (95% CI = 9.4, 11.8) among those with 6 years of education. Among women age 70, frailty-free life expectancy reaches 11.7 years (95% CI = 10.6, 12.8) among those with no education, but 13.9 years (95% CI = 12.5, 15.3) among those with 6 years.ImplicationsGiven the recent changes in educational achievement in Brazil, we believe that educational policies are powerful ways in addressing inequalities in healthy life expectancy. Public health policies aimed at avoiding the development of frailty among elderly at risk should be encouraged.

Cost-effectiveness of pembrolizumab for the adjuvant treatment of resected high-risk stage III melanoma in the United States

Aims: To evaluate the cost-effectiveness of adjuvant pembrolizumab relative to observation alone following complete resection of high-risk stage III melanoma with lymph node involvement, from a US health system perspective.Materials and methods: A Markov cohort model with four health states (recurrence-free, locoregional recurrence, distant metastases, and death) was developed to estimate costs, life-years, and quality-adjusted life-years (QALYs) associated with pembrolizumab vs observation over a lifetime (46-year) horizon. Using a parametric multi-state modeling approach, transition probabilities starting from recurrence-free were estimated based on patient-level data from KEYNOTE-054 (NCT02362594), a direct head-to-head phase 3 trial. Post-recurrence transition probabilities were informed by real-world retrospective data and clinical trials in advanced melanoma. Health state utilities and adverse event-related disutility were derived from KEYNOTE-054 trial data and published literature. Costs of drug acquisition and administration, adverse events, disease management, and terminal care were estimated in 2018 US dollars. Deterministic and probabilistic sensitivity analyses were conducted to assess robustness.Results: Over a lifetime horizon, adjuvant pembrolizumab and observation were associated with total QALYs of 9.24 and 5.95, total life-years of 10.54 and 7.15, and total costs of $489,820 and $440,431, respectively. The resulting incremental cost-effectiveness ratios (ICERs) for pembrolizumab vs observation were $15,009/QALY and $14,550/life-year. Across the range of input values and assumptions tested in deterministic sensitivity analyses, pembrolizumab ranged from being a dominant strategy to having an ICER of $57,449/QALY vs observation. The ICER was below a willingness-to-pay threshold of $100,000/QALY in 90.2% of probabilistic simulations.Limitations: Long-term extrapolation of outcomes was based on interim results from KEYNOTE-054, with a median follow-up of 15 months.Conclusions: Based on common willingness-to-pay benchmarks, pembrolizumab is highly cost-effective compared with observation alone for the adjuvant treatment of completely resected stage III melanoma in the US.

Dynamically weighted multireference perturbation theory: Combining the advantages of multi-state and state-averaged methods

We introduce two new approaches to compute near-degenerate electronic states based on the driven similarity renormalization group (DSRG) framework. The first approach is a unitary multi-state formalism based on the DSRG (MS-DSRG), whereby an effective Hamiltonian is built from a set of state-specific solutions. The second approach employs a dynamic weighting parameter to smoothly interpolate between the multi-state and the state-averaged DSRG schemes. The resulting dynamically weighted DSRG (DW-DSRG) theory incorporates the most desirable features of both multi-state approaches (ability to accurately treat many states) and state-averaged methods (correct description of avoided crossings and conical intersections). We formulate second-order perturbation theories (PT2) based on the MS- and DW-DSRG and study the potential energy curves of LiF, the conical intersection of the two lowest singlet states of NH3, and several low-lying excited states of benzene, naphthalene, and anthracene. The DW-DSRG-PT2 predicts the correct avoided crossing of LiF and avoids artifacts produced by the corresponding state-specific and multi-state theories. Excitation energies of the acenes computed with the DW-DSRG-PT2 are found to be more accurate than the corresponding state-averaged values, showing a small dependence on the number of states computed.

Optimized Control of Reversible VSC with Stability Mechanism Study in SMES Based V2G System

The superconducting magnetic energy storage (SMES)-based vehicle-to-grid (V2G) application has the characteristics of dynamic power response, well instantaneous stability and power system quality for smart power grid, and ability to reduce the standby capacity of traditional peak load adjustment and frequency modulation. And the three-phase reversible voltage source converter (VSC) is the key interface to achieve bidirectional power flow between electric vehicle and power grid. The mathematic model of active damping LCL -type VSC-based on multi-state feedback approach under the stationary αβ -coordinate system is proposed for SMES based V2G applications. And the inherent stability mechanism with the optimized control strategy influenced by the fluctuation of system parameters is analyzed. The simulation and experimental results illustrate that the V2G system achieves unity power factor and low harmonic distortion, combining with well transient performance and system robustness.

A dual frailty model for lifetime analysis in maritime transportation

We consider changes in ownership of commercial shipping vessels from an event history perspective. Each change in ownership can be influenced by the properties of the vessel itself, its age and history to date, the characteristics of both the seller and the buyer, and time-varying market conditions. Similar factors can affect the process of deciding when to scrap the vessel as no longer being economically viable. We consider a multi-state approach in which states are defined by the owning companies, a sale marks a transition, and scrapping of the vessel corresponds to moving to an absorbing state. We propose a dual frailty model that attempts to capture unexplained heterogeneity in the data, with one frailty term for the seller and one for the buyer. We describe a Monte Carlo Markov chain estimation procedure and verify its accuracy through simulations. We investigate the consequences of mistakenly ignoring frailty in these circumstances. We compare results with and without the inclusion of frailty.

Sub-hourly precise point positioning accuracy analysis – case study for selected ASG-EUPOS stations

Precise Point Positioning (PPP) is still considered a new technique of GNSS measurements intensively developed in recent years. One of the main advantages of this method is the autonomous mode of measurement, requiring only one receiver, which ensures the high accuracy of the measured position. The accuracy, in some modes of measurement and processing, is similar to the results obtained with the use of Relative GNSS technique (RGNSS). The main disadvantages of PPP include the need to introduce a set of corrections, which in the RGNSS are reduced using differential equations and a relatively long time (about 20 min or more) needed for ambiguity resolution. The analysis conducted so far concerning the determination of the PPP accuracy focused mainly on the results obtained from long (daily) static observation. The results obtained from the sub-daily observation, less often analysed, involved longer time intervals (1–8 h). In this paper, time series of position components derived from sub-hourly (30 min) PPP solutions were analysed. The analysis was based on 30 days of observations performed at 8 ASG-EUPOS system stations. For processing the collected GNSS observations (in different variants) the NAvigation Package for Earth Orbiting Satellites (NAPEOS) software was chosen. If it will be assumed that standard deviation (SD) can be a good measure of the accuracy of the obtained results, the conducted analyzes prove that the sub-hourly PPP technique can provide accuracy in the order of 0.5 cm (SD below 0.5 cm) for the horizontal position components and 1 cm (SD below 1 cm) for the vertical position component. The above accuracy was obtained in the multi-station PPP approach (fixed ambiguity solution). In float ambiguity solution scenarios the standard deviation increases up to 1 cm for horizontal components and up to 2 cm for the vertical component. The periodicity, in the obtained position components time series, were analysed using the Lomb-Scargle periodogram. Spectral analysis showed clear periodicity in the obtained results (especially for GPS-only fixed and float solutions). For GPS or GPS/GLONASS processing strategies 73% of detected periodic signals correspond to a multiple of the orbital periods of the satellites.

Does social housing reduce homelessness? A multistate analysis of housing and homelessness pathways

This article presents a multistate demographic approach for analyzing the longitudinal dynamics of housing and homelessness. The approach is applied to a sample of highly disadvantaged individuals in Australia to assess whether private housing markets and interpersonal support networks provide stable housing trajectories vis-à-vis public and community (social) housing. Discrete-time competing risk survival models are specified to estimate the probabilities of exiting housing to six housing and homeless states. Model outputs are applied to a microsimulation model to estimate the duration of episodes and the cumulative incidence of subsequent episodes of housing and homelessness. The results suggest that private housing markets carry an increased risk of housing exit relative to social housing. The homes of family and friends are the most common destination, though this type of support is usually time limited and often precipitates episodes of homelessness. These findings warrant policy consideration as to how housing markets can provide better affordability and security for low income households.

Assessing the Effectiveness of Treatment Sequences for Older Patients With High-risk Follicular Lymphoma With a Multistate Model

BackgroundDisease progression within < 2 years of initial chemoimmunotherapy and patient age > 60 years have been associated with poor overall survival (OS) in follicular lymphoma (FL). No standard treatment exists for these high-risk patients, and the effectiveness of sequential therapies remains unclear. Patients and MethodsWe studied the course of FL with first-, second-, and third-line treatment. Using large population-based data, we identified 5234 patients with FL diagnosed in 2000 to 2009. Of these patients, 71% had received second-line therapy < 2 years, and 29% had received no therapy after first-line therapy, with a median OS of < 3 years. Treatment included rituximab, R-CVP (rituximab, cyclophosphamide, vincristine), R-CHOP (rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine), R-Other (other rituximab-containing), and other regimens. The Aalen-Johansen estimator and Cox proportional hazards models were used to quantify the outcomes and assess the effects of the clinical and sociodemographic factors. ResultsR-CHOP demonstrated the most favorable 5-year OS among first- (71%), second- (55%), and third-line (61%) therapies. First-line R-CHOP improved OS (hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.50-0.64) and reduced the mortality risks after first-line (HR, 0.60; 95% CI, 0.47-0.77), second-line (HR, 0.40; 95% CI, 0.29-0.53), and third-line (HR, 0.63; 95% CI, 0.53-0.76) treatments. B-symptoms, being married, and histologic grade 1/2 were associated with the use of earlier second-line therapy. Early progression from second- to third-line therapy was associated with poor OS. The repeated use of R-CHOP or R-CVP as first- and second-line treatment yielded high 2-year mortality rates (R-CHOP + R-CHOP, 17.3%; R-CVP + R-CVP, 21.1%). ConclusionOur multistate approach assessed the effect of sequential therapy on the immediate and subsequent treatment-line outcomes. We found that R-CHOP in any line improved OS for patients with high-risk FL.