Management of Active Surveillance-Eligible Prostate Cancer during Pretransplantation Workup of Patients with Kidney Failure: A Simulation Study

A Review on Calibration Methods of Cancer Simulation Models

Calibration, a critical step in the development of simulation models, involves adjusting unobservable parameters to ensure that the outcomes of the model closely align with observed target data. This process is particularly vital in cancer simulation models with a natural history component where direct data to inform natural history parameters are rarely available. This work reviews the literature of cancer simulation models with a natural history component and identifies the calibration approaches used in these models with respect to the following attributes: calibration target, goodness-of-fit (GOF) measure, parameter search algorithm, acceptance criteria, and stopping rules. After a comprehensive search of the PubMed database from 1981 to June 2023, 68 studies were included in the review. Nearly all (n=66) articles specified the calibration targets, and most articles (n=56) specified the parameter search algorithms they used, whereas goodness-of-fit metric (n=51) and acceptance criteria/stopping rule (n=45) were reported for fewer times. The most frequently used calibration targets were incidence, mortality, and prevalence, whose data sources primarily come from cancer registries and observational studies. The most used goodness-of-fit measure was weighted mean squared error. Random search has been the predominant method for parameter search, followed by grid search and Nelder-mead method. Machine learning-based algorithms, despite their fast advancement in the recent decade, has been underutilized in the cancer simulation models. More research is needed to compare different parameter search algorithms used for calibration.

Key points

This work reviewed the literature of cancer simulation models with a natural history component and identified the calibration approaches used in these models with respect to the following attributes: calibration target, goodness-of-fit (GOF) measure, parameter search algorithm, acceptance criteria, and stopping rules.Random search has been the predominant method for parameter search, followed by grid search and Nelder-mead method.Machine learning-based algorithms, despite their fast advancement in the recent decade, has been underutilized in the cancer simulation models. Furthermore, more research is needed to compare different parameter search algorithms used for calibration.

Quality-adjusted life years and surgical waiting list: Systematic review of the literature

BACKGROUND

The quality-adjusted life year (QALY) is a metric that is increasingly used today in the field of health economics to evaluate the value of different medical treatments and procedures. Surgical waiting lists (SWLs) represent a pressing problem in public healthcare. The QALY measure has rarely been used in the context of surgery. It would be interesting to know how many QALYs are lost by patients on SWLs.

AIM

To investigate the relationship between QALYs and SWLs in a systematic review of the scientific literature.

METHODS

The study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement. An unlimited search was carried out in PubMed, updated on January 19, 2024. Data on the following variables were investigated and analyzed: Specialty, country of study, procedure under study, scale used to measure QALYs, the use of a theoretical or real-life model, objectives of the study and items measured, the economic value assigned to the QALY in the country in question, and the results and conclusions published.

RESULTS

Forty-eight articles were selected for the study. No data were found regarding QALYs lost on SWLs. The specialties in which QALYs were studied the most in relation to the waiting list were urology and general surgery, with 15 articles each. The country in which the most studies of QALYs were carried out was the United States (n = 21), followed by the United Kingdom (n = 9) and Canada (n = 7). The most studied procedure was organ transplantation (n = 39), including 15 kidney, 14 liver, 5 heart, 4 lung, and 1 intestinal. Arthroplasty (n = 4), cataract surgery (n = 2), bariatric surgery (n = 1), mosaicplasty (n = 1), and septoplasty (n = 1) completed the surgical interventions included. Thirty-nine of the models used were theoretical (the most frequently applied being the Markov model, n = 34), and nine were real-life. The survey used to measure quality of life in 11 articles was the European Quality of Life-5 dimensions, but in 32 articles the survey was not specified. The willingness-to-pay per QALY gained ranged from $100000 in the United States to €20000 in Spain.

CONCLUSION

The relationship between QALYs and SWLs has only rarely been studied in the literature. The rate of QALYs lost on SWLs has not been determined. Future research is warranted to address this issue.

The Difference Method Approach for Sampling Order Constrained Parameters: An Improved Implementation and Important Limitations

A health economic model may include a set of related inputs whose true values are uncertain, but that can be assumed to follow a logical order. Various approaches are available for performing probabilistic sensitivity analysis while preserving the order constraint, one such approach is known as the difference method. The difference method approach appears to have many of the required properties, has been endorsed by good practice guidelines, and is likely to prove a popular approach. However, the proposed implementation of the difference method approach is cumbersome, requiring numerical estimation, which might present a barrier to its adoption. Furthermore, it is unclear whether the method can always be applied to three or more model inputs and whether it is unbiased across all possible input values. This study has investigated these three issues for ordered inputs bounded between 0 and 1. An analytic solution is given that allows for more straightforward and compact implementation. The difference method approach cannot always be applied to a set of three or more model inputs, and this depends on the relative size of the variances of the logit-transformed Beta distributions fitted to each variable. The approach can also produce samples with biased means and variances under certain combinations of input means and variances. It is recommended that the difference method approach be used where appropriate; however, an understanding of its limitations is necessary to identify such cases.

Prostate Cancer in Transplant Receivers-A Narrative Review on Oncological Outcomes

Prostate cancer (PCa) is a low tumor mutational burden (TMB) cancer with a poor response to immunotherapy. Nonetheless, immunotherapy can be useful, especially in metastatic castration-resistant PCa (mCRPC). Increased cytotoxic T lymphocytes (CTLs) density is correlated with a shorter overall survival (OS), an early biochemical relapse, and a generally poor PCa prognosis. An increased number of CCR4+ regulatory T cells (CCR4 + Tregs) relates to a higher Gleason score or earlier progression. The same therapeutic options are available for renal transplant recipients (RTRs) as for the population, with a comparable functional and oncological outcome. Radical retropubic prostatectomy (RRP) is the most common method of radical treatment in RTRs. Brachytherapy and robot-assisted radical prostatectomy (RARP) seem to be promising therapies. Further studies are needed to assess the need for prostatectomy in low-risk patients before transplantation. The rate of adverse pathological features in RTRs does not seem to differ from those observed in the non-transplant population and the achieved cancer control seems comparable. The association between PCa and transplantation is not entirely clear. Some researchers indicate a possible association between a more frequent occurrence of PCa and a worse prognosis in advanced or metastatic PCa. However, others claim that the risk and survival prognosis is comparable to the non-transplant population.

Impact of newly diagnosed prostate cancer at time of evaluation for renal transplantation

Systematic screening for prostate cancer is widely recommended in candidates for renal transplant at the time of listing. There are concerns that overdiagnosis of low-risk prostate cancer may result in reducing access to transplant without demonstrated oncological benefits. The objective of the study was to assess the outcome of newly diagnosed prostate cancer in candidates for transplant at the time of listing, and its impact on transplant access and transplant outcomes according to treatment options. This retrospective study was conducted over 10 years in 12 French transplant centers. Patients included were candidates for renal transplant at the time of prostate cancer diagnosis. Demographical and clinical data regarding renal disease, prostate cancer, and transplant surgery were collected. The primary outcome of the study was the interval between prostate cancer diagnosis and active listing according to treatment options. Overall median time from prostate cancer diagnosis to active listing was 25.0 months [16.4-40.2], with statistically significant differences in median time between the radiotherapy and the active surveillance groups (p = .03). Prostate cancer treatment modalities had limited impact on access and outcome of renal transplantation. Active surveillance in low-risk patients does not seem to compromise access to renal transplantation, nor does it impact oncological outcomes.

Treatment patterns and survival of low and intermediate-risk prostate cancer in end-stage kidney disease: A retrospective population cohort study

BACKGROUND

In accordance with guidelines, observation with or without active surveillance for low-risk prostate cancer increased in recent years in the general population. We compared treatment patterns and mortality for low- and intermediate-risk prostate cancer and mortality rates among end-stage kidney disease (ESKD) and non-ESKD patients.

METHODS

This is a retrospective population-based observational cohort study of Surveillance, Epidemiology, and End Results-Medicare data of men aged 66 years and older with localized prostate cancer (2004-2015). ESKD status was determined using Medicare billing codes. Multivariable logistic regression models and Cox-proportional hazards models were used to study definitive treatment patterns and mortality, respectively.

RESULTS

For low-risk prostate cancer, dialysis patients (N = 83) had lower but not statistically significant odds (OR, 0.74; 95% CI: 0.48-1.16) of receiving definitive treatment than non-ESKD patients (N = 24,935). For those with intermediate-risk prostate cancer, dialysis patients (N = 254) had lower odds to receive definitive treatment (OR, 0.54; 95% CI: 0.42-0.72) than non-ESKD patients (N = 60,883). From 2004-2010 to 2011-2015, for patients with low-risk prostate cancer, while the receipt of definitive treatment for non-ESKD patients trended down from 72% to 48%, it trended up for dialysis patients from 55% to 65%. Kidney transplant patients (N = 33 for low-risk and N = 91 for intermediate-risk) had lower rates of definitive treatment for low-risk and similar rates of treatment for intermediate-risk prostate cancer compared to non-ESKD patients.

CONCLUSIONS

The disparity in definitive treatment rates for low-risk prostate cancer among dialysis patients exists despite their high mortality, compared to the general population.

Cancer Screening in Solid Organ Transplant Recipients: A Focus on Screening Liver, Lung, and Kidney Recipients for Cancers Related to the Transplanted Organ

Over the last few decades, the life expectancy of solid organ transplant recipients (SOTRs) has improved significantly. With SOTRs living longer, more recipients are dying from cancer. There is a reported 2- to 3-fold increased risk of cancer-specific mortality in SOTRs compared with the general population. Cancer in an SOTR can be de novo, recurrent, or donor-derived. Cancer screening in this population is crucial, as early detection and treatment may improve outcomes. In the absence of randomized controlled trials dedicated to SOTRs, clinicians rely on clinical practice guidelines from regional and national transplant societies; however, these may vary considerably across jurisdictions and transplanted organ. At present, no widely accepted consensus exists for cancer screening protocols in SOTRs, particularly with regard to screening for malignancy related to transplanted organ. Some SOTRs may be at higher risk of malignancies within the allograft. This is particularly the case in lung and liver recipients, though less common in kidney recipients who are at increased risk of developing renal cell cancer in their native kidneys. This increased risk has not been uniformly incorporated into screening recommendations for SOTRs. In this review, we summarize the cancer screening recommendations for SOTRs from various transplant organizations based on transplanted organ. This review also discusses the complexity and controversies surrounding screening of cancer in the allograft and future avenues to improve cancer detection in this context. More studies specific to SOTRs are required to form generalizable and evidence-based cancer screening guidelines, particularly with respect to cancer screening in the allograft.

Kidney and pancreas transplant candidacy

PURPOSE OF REVIEW

Kidney and/or pancreas transplantation candidacy criteria have evolved significantly over time reflecting improved pre and post-transplant management. With improvement in medical care, potential candidates for transplant not only are older but also have complex medical issues. This review focuses on the latest trends regarding candidacy for kidney and/or pancreas transplantation along with advances in pretransplant cardiac testing.

RECENT FINDINGS

More candidates are now eligible for kidney and/or pancreas transplantation owing to less stringent candidacy criteria especially in regards to age, obesity, frailty and history of prior malignancy. Pretransplant cardiovascular assessment has also come a long way with a focus on less invasive strategies to assess for coronary artery disease.

SUMMARY

Criteria for kidney and/or pancreas transplantation are expanding. Patients who in the past might have been declined because of numerous factors are now finding that transplant centers are more open minded to their candidacy, which could lead to better access to organ transplant wait list.

Waiting times in renal transplant candidates with a history of malignancy: time for a change?

PURPOSE OF REVIEW

With the aging population of kidney transplant candidates, a history of malignancy is an increasingly prevalent finding. Tumors can constitute a contraindication for transplantation or can lead to a delay of acceptance to the waiting-list. Current waiting time guidelines mainly refer to early data collected nearly 30 years ago, when the knowledge on tumors was, by current standards, still limited.

RECENT FINDINGS

Today, cancers can usually be divided into many different biological subtypes, according to histological and molecular subclassification and the availability of genetic testing. A more precise stratification and targeted antitumor therapies have led to better therapy outcomes or even cures from certain malignancies and to a better appreciation of tumor risks for the patient.

SUMMARY

Even though transplant patients do have an increased risk for malignancies, it is often overlooked that patients, while on dialysis, are equally prone to develop a tumor. Competing risks (e.g. cardiovascular, mortality risks) through prolonged time on dialysis have to be equally considered, when the decision for acceptance of a patient to the waiting-list is made. Current waiting time suggestions should be critically reconsidered for every patient after a thorough discussion with an oncologist, including new diagnostic and therapeutic strategies, as well as novel risk stratifications.