Quantifying the Transition from Active Surveillance to Watchful Waiting Among Men with Very Low-risk Prostate Cancer

AbstractBackgroundActive surveillance (AS) is commonly used for men with low-risk prostate cancer (PCa). When life expectancy becomes too short for curative treatment to be beneficial, a change from AS to watchful waiting (WW) follows. Little is known about this change since it is rarely documented in medical records.ObjectiveTo model transition from AS to WW and how this is affected by age and comorbidity among men with very low-risk PCa.Design, setting, and participantsNational population-based healthcare registers were used for analysis.Outcome measurements and statistical analysisUsing data on PCa characteristics, age, and comorbidity, a state transition model was created to estimate the probability of changes between predefined treatments to estimate transition from AS to WW.Results and limitationsOur estimates indicate that 48% of men with very low-risk PCa starting AS eventually changed to WW over a life course. This proportion increased with age at time of AS initiation. Within 10 yr from start of AS, 10% of men aged 55 yr and 50% of men aged 70 yr with no comorbidity at initiation changed to WW. Our prevalence simulation suggests that the number of men on WW who were previously on AS will eventually stabilise after 30 yr. A limitation is the limited information from clinical follow-up visits (eg, repeat biopsies).ConclusionsWe estimated that changes from AS to WW become common among men with very low-risk PCa who are elderly. This potential change to WW should be discussed with men starting on AS. Moreover, our estimates may help in planning health care resources allocated to men on AS, as the transition to WW is associated with lower demands on outpatient resources.Patient summaryChanges from active surveillance to watchful waiting will become more common among men with very low-risk prostate cancer. These observations suggest that patients need to be informed about this potential change before they start on active surveillance

A literature review to understand health literacy in men with prostate cancer on active surveillance

Background and Objective: Active surveillance (AS) has been established as an important treatment option for patients with localised prostate cancer (PCa). Current evidence suggests that health literacy is an important facilitator or barrier to choosing and adhering to AS. We aim to understand how the level of health literacy has an impact on choosing and adhering to AS for PCa patients. Methods: We performed a narrative literature review in accordance with the Narrative Review guidelines through the MEDLINE online database via PubMed using two different search strategies to identify the relevant literature. We looked at literature until August 2022. A narrative synthesis was performed to identify if there is any evidence on how studies report health literacy as an outcome in the AS population and if there are any interventions targeting health literacy. Key Content and Findings: We identified 18 studies which looked at health literacy in the PCa context. Health literacy was measured in the context of comprehension of information of patients across PCa stages, decision making across PCa stages and quality of life (QoL) across PCa stages. Lower health literacy had a negative impact on the identified themes. Nine of the identified studies used validated health literacy measures. Interventions targeting health literacy have been used to improve health literacy with a positive impact across the patient journey. Conclusions: Health literacy plays an important role in enabling men to take an active part in their treatment journey. In this review, we presented how health literacy is measured and which interventions targeting health literacy are implemented across PCa. These examples of interventions targeting health literacy should be studied further and translated into the AS setting to improve treatment decision making and adherence to AS.</p

A first step towards a global nomogram to predict disease progression for men on active surveillance

Background: Signs of disease progression (28%) and conversion to active treatment without evidence of disease progression (13%) are the main reasons for discontinuation of active surveillance (AS) in men with localised prostate cancer (PCa). We aimed to develop a nomogram to predict disease progression in these patients. Methods: As a first step in the development of a nomogram, using data from Movembers' GAP3 Consortium (n=14,380), we assessed heterogeneity between centres in terms of risk of disease progression. We started with assessment of baseline hazards for disease progression based on grouping of centres according to follow-up protocols [high: yearly; intermediate: similar to 2 yearly; and low: at year 1, 4 & 7 (i.e., PRIAS)]. We conducted cause-specific random effect Cox proportional hazards regression to estimate risk of disease progression by centre in each group. Results: Disease progression rates varied substantially between centres [median hazard ratio (MHR): 2.5]. After adjustment for various clinical factors (age, year of diagnosis, Gleason grade group, number of positive cores and PSA), substantial heterogeneity in disease progression remained between centres. Conclusions: When combining worldwide data on AS, we noted unexplained differences of disease progression rate even after adjustment for various clinical factors. This suggests that when developing a global nomogram, local adjustments for differences in risk of disease progression and competing outcomes such as conversion to active treatment need to be considered.Peer reviewe

Теоретические аспекты формирования и содержание организационно–экономического механизма функционирования интегрированных структур в АПК

Background: The presence of comorbid conditions is strongly related to survival and also affects treatment choices in cancer patients. This comorbidity is often quantified by the Charlson Comorbidity Index (CCI) using specific weights (1, 2, 3, or 6) for different comorbidities. It has been shown that the CCI increases at different times and with different sizes, so that traditional time to event analysis is not adequate to assess these temporal changes. Here, we present a method to model temporal changes in CCI in cancer patients using data from PCBaSe Sweden, a nation-wide population-based prospective cohort of men diagnosed with prostate cancer. Our proposed model is based on the assumption that a change in comorbidity, as quantified by the CCI, is an irreversible one-way process, i.e., CCI accumulates over time and cannot decrease. Methods: CCI was calculated based on 17 disease categories, which were defined using ICD-codes for discharge diagnoses in the National Patient Register. A state transition model in discrete time steps (i.e., four weeks) was applied to capture all changes in CCI. The transition probabilities were estimated from three modelling steps: 1) Logistic regression model for vital status, 2) Logistic regression model to define any changes in CCI, and 3) Poisson regression model to determine the size of CCI change, with an additional logistic regression model for CCI changes &gt;= 6. The four models combined yielded parameter estimates to calculate changes in CCI with their confidence intervals. Results: These methods were applied to men with low-risk prostate cancer who received active surveillance (AS), radical prostatectomy (RP), or curative radiotherapy (RT) as primary treatment. There were large differences in CCI changes according to treatment. Conclusions: Our method to model temporal changes in CCI efficiently captures changes in comorbidity over time with a small number of regression analyses to perform - which would be impossible with tradition time to event analyses. However, our approach involves a simulation step that is not yet included in standard statistical software packages. In our prostate cancer example we showed that there are large differences in development of comorbidities among men receiving different treatments for prostate cancer

Systematic review of the association between socioeconomic status and bladder cancer survival with hospital type, comorbidities, and treatment delay as mediators

Objectives:  To review the current evidence on the relationship between three proposed mediators (comorbidities, hospital type, and treatment delays) for the relationship between socioeconomic status (SES) and bladder cancer survival. Materials and methods:  Six different searches using OVID (Medline and Embase) were carried out to collate information available between the proposed mediators with both SES and survival in bladder cancer. This systematic review was conducted according to a pre-defined protocol and in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results:  A total of 49 studies were included in the review across the six searches (one appeared in two searches). There was a wealth of studies investigating the relationship between each of the proposed mediators with survival in bladder cancer patients. In general, a higher SES, lower comorbidities, and a larger hospital volume were all found to be associated with a decreased risk of death in bladder cancer patients. There was, however, a paucity of studies investigating the associations between these mediators and SES in bladder cancer patients. Conclusions:  To gain a deeper understanding of the relationship between SES and survival identified in several observational studies, further investigations into the relationship between the proposed mediators and SES are warranted. Moreover, modifiable mediators, eg, treatment delay, highlight the importance of the standardization of clinical care across SES groups for all bladder cancer patients