ackground. The epidemiological impact of public health interventions targeted at reducing transmission of human immunodeficiency virus type 1 (HIV-1) during early or late-stage infection depends on the contribution of these disease stages to transmission within a particular epidemic.

Methods. Transmission hazards and durations of periods of high infectivity during primary, asymptomatic, and late-stage infection were estimated for HIV-1-serodiscordant heterosexual couples in Rakai, Uganda, by use of a robust probabilistic framework.

Results. Primary infection and late-stage infection were estimated to be 26 and 7 times, respectively, more infectious than asymptomatic infection. High infectiousness during primary infection was estimated to last for ∼3 months after seroconversion, whereas high infectiousness during late-stage infection was estimated to be concentrated between 19 months and 10 months before death.

Conclusions. Primary and late-stage HIV-1 infection are more infectious than previously estimated, but for shorter periods. In a homogeneous population, the asymptomatic stage of infection will typically contribute more to the net transmission of HIV-1 over the lifetime of an infected individual, because of its longer duration. The dependence of the relative contribution of infectious stages on patterns of sexual behavior and the phase of epidemics is discussed.

https://www.who.int/hiv/events/artprevention/hollingsworth.pdf

HIV-1 transmission, by stage of infection.

ContextHomosexual and bisexual men infected with human
immunodeficiency virus (HIV) are at increased risk for human
papillomavirus–related anal neoplasia and anal squamous cell carcinoma
(SCC).ObjectiveTo estimate the clinical benefits and
cost-effectiveness of screening HIV-positive homosexual and bisexual
men for anal squamous intraepithelial lesions (ASIL) and anal SCC.DesignCost-effectiveness analysis performed from a societal
perspective that used reference case recommendations from the Panel on
Cost-Effectiveness in Health and Medicine. A state-transition Markov
model was developed to calculate lifetime costs, life expectancy, and
quality-adjusted life expectancy for no screening vs several screening
strategies for ASIL and anal SCC using anal Papanicolaou (Pap) testing
at different intervals. Values for incidence, progression, and
regression of anal neoplasia; efficacy of screening and treatment;
natural history of HIV; health-related quality of life; and costs were
obtained from the literature.Setting and ParticipantsHypothetical cohort of homosexual and
bisexual HIV-positive men living in the United States.Main Outcome MeasuresLife expectancy, quality-adjusted life
expectancy, quality-adjusted years of life saved, lifetime costs, and
incremental cost-effectiveness ratio.ResultsScreening for ASIL increased quality-adjusted life
expectancy at all stages of HIV disease. Screening with anal Pap tests
every 2 years, beginning in early HIV disease (CD4 cell count
>0.50×109/L), resulted in a 2.7-month
gain in quality-adjusted life expectancy for an incremental
cost-effectiveness ratio of $13,000 per quality-adjusted life
year saved. Screening with anal Pap tests yearly provided additional
benefit at an incremental cost of $16,600 per quality-adjusted
life year saved. If screening was not initiated until later in the
course of HIV disease (CD4 cell count
<0.50×109/L), then yearly Pap test
screening was preferred due to the greater amount of prevalent anal
disease (cost-effectiveness ratio of less than $25,000 per
quality-adjusted life year saved compared with no screening). Screening
every 6 months provided little additional benefit over that of yearly
screening. Results were most sensitive to the rate of progression of
ASIL to anal SCC and the effectiveness of treatment of precancerous
lesions.ConclusionsScreening HIV-positive homosexual and bisexual men for
ASIL and anal SCC with anal Pap tests offers quality-adjusted life
expectancy benefits at a cost comparable with other accepted clinical
preventive interventions.

https://jamanetwork.com/journals/jama/articlepdf/189987/joc81560.pdf

The clinical effectiveness and cost-effectiveness of screening for anal squamous intraepithelial lesions in homosexual and bisexual HIV-positive men.

ContextCervical cancer is a leading cause of cancer-related death among women
in developing countries. In such low-resource settings, cytology-based screening
is difficult to implement, and less complex strategies may offer additional
options.ObjectiveTo assess the cost-effectiveness of several cervical cancer screening
strategies using population-specific data.Design and SettingCost-effectiveness analysis using a mathematical model and a hypothetical
cohort of previously unscreened 30-year-old black South African women. Screening
tests included direct visual inspection (DVI) of the cervix, cytologic methods,
and testing for high-risk types of human papillomavirus (HPV) DNA. Strategies
differed by number of clinical visits, screening frequency, and response to
a positive test result. Data sources included a South African screening study,
national surveys and fee schedules, and published literature.Main Outcome MeasuresYears of life saved (YLS), lifetime costs in US dollars, and incremental
cost-effectiveness ratios (cost per YLS).ResultsWhen analyzing all strategies performed as a single lifetime screen
at age 35 years compared with no screening, HPV testing followed by treatment
of screen-positive women at a second visit, cost $39/YLS (27% cancer incidence
reduction); DVI, coupled with immediate treatment of screen-positive women
at the first visit was next most effective (26% cancer incidence reduction)
and was cost saving; cytology, followed by treatment of screen-positive women
at a second visit was least effective (19% cancer incidence reduction) at
a cost of $81/YLS. For any given screening frequency, when strategies were
compared incrementally, HPV DNA testing generally was more effective but also
more costly than DVI, and always was more effective and less costly than cytology.
When comparing all strategies simultaneously across screening frequencies,
DVI was the nondominated strategy up to a frequency of every 3 years (incremental
cost-effectiveness ratio, $460/YLS), and HPV testing every 3 years (incremental
cost-effectiveness ratio, $11 500/YLS) was the most effective strategy.ConclusionCervical cancer screening strategies that incorporate DVI or HPV DNA
testing and eliminate colposcopy may offer attractive alternatives to cytology-based
screening programs in low-resource settings.

https://jamanetwork.com/journals/jama/articlepdf/193957/JOC10234.pdf

Policy analysis of cervical cancer screening strategies in low-resource settings: clinical benefits and cost-effectiveness.

Survival analysis (time-to-event analysis) is widely used in economics and finance, engineering, medicine and many other areas. A fundamental problem is to understand the relationship between the covariates and the (distribution of) survival times(times-to-event). Much of the previous work has approached the problem by viewing the survival time as the first hitting time of a stochastic process, assuming a specific form for the underlying stochastic process, using available data to learn the relationship between the covariates and the parameters of the model, and then deducing the relationship between covariates and the distribution of first hitting times (the risk). However, previous models rely on strong parametric assumptions that are often violated. This paper proposes a very different approach to survival analysis, DeepHit, that uses a deep neural network to learn the distribution of survival times directly.DeepHit makes no assumptions about the underlying stochastic process and allows for the possibility that the relationship between covariates and risk(s) changes over time. Most importantly, DeepHit smoothly handles competing risks; i.e. settings in which there is more than one possible event of interest.Comparisons with previous models on the basis of real and synthetic datasets demonstrate that DeepHit achieves large and statistically significant performance improvements over previous state-of-the-art methods.

/pdf/deephit-a-deep-learning-approach-to-survival-analysis-with-1m56wooqn2.pdf

DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks

Summary. Many chronic diseases have a natural interpretation in terms of staged progression. Multistate models based on Markov processes are a well-established method of estimating rates of transition between stages of disease. However, diagnoses of disease stages are sometimes subject to error. The paper presents a general hidden Markov model for simultaneously estimating transition rates and probabilities of stage misclassification. Covariates can be fitted to both the transition rates and the misclassification probabilities. For example, in the study of abdominal aortic aneurysms by ultrasonography, the disease is staged by severity, according to successive ranges of aortic diameter. The model is illustrated on data from a trial of aortic aneurysm screening, in which the screening measurements are subject to error. General purpose software for model implementation has been developed in the form of an R package and is made freely available.

/pdf/multistate-markov-models-for-disease-progression-with-4twd04f5f5.pdf

Multistate Markov models for disease progression with classification error

We use a staged Markov model to estimate the distribution and mean length of the incubation period for acquired immunodeficiency syndrome (AIDS) from a cohort of 603 human immunodeficiency virus (HIV) infected individuals who have been followed through various stages of infection. The model partitions the infected period into four progressive stages: (1) infected but antibody-negative; (2) antibody-positive but asymptomatic; (3) pre-AIDS symptoms and/or abnormal haematologic indicator; and (4) clinical AIDS. We also model a fifth stage: death due to AIDS. The estimated mean (median) waiting times in each stage of infection are stage 1, 2.2 (1.5) months; stage 2, 52.6 (36.5) months; stage 3, 62.9 (43.6) months; and stage 4, 23.6(16.3) months. We estimate the mean AIDS incubation period (from infection to development of clinical AIDS) as 9.8 years with a 95 per cent confidence interval of [8.4, 11.2] years. The paper also considers the estimated density function of the AIDS incubation period and the estimated survival functions for individuals in each stage of infection. This work represents one of the most complete statistical descriptions to date of the natural history of HIV infection.

Lemp Gf

Papers

Statistical analysis of the stages of HIV infection using a Markov model