Prostate cancer incidence and mortality in Portugal: trends, projections and regional differences

Real‑world retrospective study of early‑stage prostate cancer at a Portuguese Comprehensive Cancer Centre: The PEarlC study

Despite the high prevalence of localised prostate cancer (LPC) and locally advanced prostate cancer (LAPC), evidence on the characteristics of patients, treatments and clinical outcomes stratified by disease risk is limited. The PEarlC study was conducted to characterise a cohort of patients with early-stage prostate cancer that included real-world clinical outcomes. Retrospective data from a cohort of patients diagnosed with LPC/LAPC between 2015 and 2017 and followed up until December 2020 at a Portuguese comprehensive cancer centre (IPO Porto) was analysed. Patients were classified as LPC (high- or non-high-risk) or LAPC according to European Association of Urology guidelines, were eligible if diagnosed at stage I-III and followed up in Urology, Medical Oncology or Radiation Oncology outpatient clinics of IPO Porto. Data was collected from the medical/administrative records database. Clinical outcomes included prostate-specific antigen (PSA) progression-free survival, metastasis-free survival, disease-free survival, progression-free survival, overall survival (OS), PSA response (palliative) and no evidence of residual tumour (prostatectomy). Time-to-event outcomes were compared between subgroups using the log-rank test. A total of 790 patients were included (54.8% non-high-risk LPC, 30.9% high-risk LPC, 14.3% LAPC) and the median follow-up was 46.7 months. Patients had a median age of 68.0 years. The majority of patients were stage II (52.9%) and Eastern Cooperative Oncology Group 0-1 (99.9%) and received treatment with curative intent (85.4%). The median was only achieved in progression-free survival (29.9 months; 95% CI, 26.5-41.0 months), as evaluated in palliative patients. At year 5, 82.9% were free of PSA progression (curative), 87.5% were metastasis-free, 83.7% were disease-free, all patients in palliative treatment progressed and the 5-year OS rate was 92.9% (CI 95%, 90.2-95.7%). Among patients with LPC, OS was worse in high-risk vs. non-high-risk patients (5-year OS rate, 88.8% vs. 96.8%; hazard ratio=3.34, CI 95%, 1.64-7.05; P=0.001). PSA response rate was 81.4% in the palliative setting. There was no evidence of residual tumour in 61.6% of patients who underwent prostatectomy. Although most patients with early-stage prostate cancer treated at IPO Porto showed positive 5-year real-world outcomes, patients with high-risk LPC showed worse OS compared with patients with non-high-risk LPC and therefore a poorer prognosis. The present large-sample real-world study is an important contribution to reducing the evidence gap on prostate cancer.

Prostate cancer treatment in Portugal: a nationwide analysis

Different treatment options exist for localized prostate cancer. Treatments performed in high-volume hospitals are associated with better results. Our objective was to describe time trends in prostate cancer treatments in Portugal and case volume per hospital. We used the national database of diagnosis-related group of the Portuguese Central Administration of the Health System to describe the number of radical prostatectomy (RP), brachytherapy (BT) and external radiotherapy (eRT) treatments performed in all National Health System hospitals. There was a rapid increase in the annual number of RP until 2006 and then a deceleration; BT treatments augmented significantly until 2011. The utilization of eRT also increased, surpassing RP after 2010. From the 46 hospitals performing RP, only eight had a case-volume > 50 treatments/year, and from the nine hospitals performing BT, only four accomplished > 15 treatments/year. In the 11 hospitals with eRT, nine performed > 50/year. Regarding RP, there was negative correlation between the hospital volume and length of stay (r = - 0.303; p = 0.041). In the Portuguese National Health Service there was a steep increase in the number of prostate cancer treatments, and there is an ample margin for concentration of RP and BT treatments, for improvement of the hospitals case volume.

Early biomarkers of extracapsular extension of prostate cancer using MRI-derived semantic features

BACKGROUND

To construct a model based on magnetic resonance imaging (MRI) features and histological and clinical variables for the prediction of pathology-detected extracapsular extension (pECE) in patients with prostate cancer (PCa).

METHODS

We performed a prospective 3 T MRI study comparing the clinical and MRI data on pECE obtained from patients treated using robotic-assisted radical prostatectomy (RARP) at our institution. The covariates under consideration were prostate-specific antigen (PSA) levels, the patient's age, prostate volume, and MRI interpretative features for predicting pECE based on the Prostate Imaging-Reporting and Data System (PI-RADS) version 2.0 (v2), as well as tumor capsular contact length (TCCL), length of the index lesion, and prostate biopsy Gleason score (GS). Univariable and multivariable logistic regression models were applied to explore the statistical associations and construct the model. We also recruited an additional set of participants-which included 59 patients from external institutions-to validate the model.

RESULTS

The study participants included 184 patients who had undergone RARP at our institution, 26% of whom were pECE+ (i.e., pECE positive). Significant predictors of pECE+ were TCCL, capsular disruption, measurable ECE on MRI, and a GS of ≥7(4 + 3) on a prostate biopsy. The strongest predictor of pECE+ is measurable ECE on MRI, and in its absence, a combination of TCCL and prostate biopsy GS was significantly effective for detecting the patient's risk of being pECE+. Our predictive model showed a satisfactory performance at distinguishing between patients with pECE+ and patients with pECE-, with an area under the ROC curve (AUC) of 0.90 (86.0-95.8%), high sensitivity (86%), and moderate specificity (70%).

CONCLUSIONS

Our predictive model, based on consistent MRI features (i.e., measurable ECE and TCCL) and a prostate biopsy GS, has satisfactory performance and sufficiently high sensitivity for predicting pECE+. Hence, the model could be a valuable tool for surgeons planning preoperative nerve sparing, as it would reduce positive surgical margins.

Machine learning in predicting extracapsular extension (ECE) of prostate cancer with MRI: a protocol for a systematic literature review

INTRODUCTION

In patients with prostate cancer (PCa), the detection of extracapsular extension (ECE) and seminal vesicle invasion is not only important for selecting the appropriate therapy but also for preoperative planning and patient prognosis. It is of paramount importance to stage PCa correctly before surgery, in order to achieve better surgical and outcome results. Over the last years, MRI has been incorporated in the classical prostate staging nomograms with clinical improvement accuracy in detecting ECE, but with variability between studies and radiologist's experience.

METHODS AND ANALYSIS

The research question, based on patient, index test, comparator, outcome and study design criteria, was the following: what is the diagnostic performance of artificial intelligence algorithms for predicting ECE in PCa patients, when compared with that of histopathological results after radical prostatectomy. To answer this question, we will use databases (EMBASE, PUBMED, Web of Science and CENTRAL) to search for the different studies published in the literature and we use the QUADA tool to evaluate the quality of the research selection.

ETHICS AND DISSEMINATION

This systematic review does not require ethical approval. The results will be disseminated through publication in a peer-review journal, as a chapter of a doctoral thesis and through presentations at national and international conferences.

PROSPERO REGISTRATION NUMBER

CRD42020215671.

Spatial and temporal patterns of prostate cancer burden and their association with Socio-Demographic Index in Asia, 1990-2019

BACKGROUND

Prostate cancer is the second most frequently diagnosed cancer for males worldwide, but the spatial and temporal trends of prostate cancer burden remain unknown in Asia. This study aimed to investigate the changing spatial and temporal trends of incidence, prevalence, mortality, disability-adjusted life year (DALY), and mortality-to-incidence ratio (MIR) of prostate cancer, and their association with the Socio-Demographic Index (SDI) in 48 Asian countries from 1990 to 2019.

METHODS

Data were extracted from the Global Health Data Exchange query tool, covering 48 Asian countries from 1990 to 2019. The average annual percent change was calculated to evaluate temporal trends. Spatial autocorrelation analysis was used to obtain spatial patterns, and the association between SDI and prostate cancer burden was estimated using a spatial panel model.

RESULTS

In Asia, the age-standardized incidence and prevalence of prostate cancer increased in almost all countries, and its mortality and DALY also increased in over half of the countries. Significantly regional disparities were found in Asia, and the hot spots for incidence, prevalence, mortality, and DALY were all located in Western Asia, the hot spots of percent change also occurred in Western Asia for incidence and DALY. Furthermore, SDI had a positive association with mortality (coef = 2.51, 95% confidence interval [CI]: 2.13-2.90) and negative association with DALY (coef = -14.99, 95% CI: -20.37 to -9.60) and MIR (coef = -0.95, 95%CI: -0.99 to -0.92).

CONCLUSIONS

Prostate cancer burden increased rapidly throughout Asia and substantial disparities had persisted between countries. Geographically targeted interventions are needed to reduce the prostate cancer burden throughout Asia and in specific countries.

A Review of Capture-recapture Methods and Its Possibilities in Ophthalmology and Vision Sciences

Epidemiological information is expected to be used to develop key aspects of eye care such as to control and minimise the impact of diseases, to allocate resources, to monitor public health actions, to determine the best treatment options and to forecast the consequence of diseases in populations. Epidemiological studies are expected to provide information about the prevalence and/or incidence of eye diseases or conditions. To determine prevalence is necessary to perform a cross-sectional screening of the population at risk to ascertain the number of cases. The aim of this review is to describe and evaluate capture-recapture methods (or models) to ascertaining the number of individuals with a disease (e.g. diabetic retinopathy) or condition (e.g. vision impairment) in the population. The review covers the fundamental aspects of capture-recapture methods that would enable non-experts in epidemiology to use it in ophthalmic studies. The review provides information about theoretical aspects of the method with examples of studies in ophthalmology in which it has been used. We also provide a problem/solution approach for limitations arising from the lists obtained from registers or other reliable sources. We concluded that capture-recapture models can be considered reliable to estimate the total number of cases with eye conditions using incomplete information from registers. Accordingly, the method may be used to maintain updated epidemiological information about eye conditions helping to tackle the lack of surveillance information in many regions of the globe.

Pain prevalence and treatment in patients with metastatic bone disease

The accomplishment of successful pain treatment requires evaluation, characterization and quantification. The present study characterized pain and survival in a cohort of patients with cancer with bone metastasis who were treated with intravenous bisphosphonates. A total of 84 patients self-completed the Brief Pain Inventory (BPI) and 36-Item Short Form Survey (SF-36), between November 2010 and March 2011 with a 5-year survival follow-up as a surrogate marker of cancer burden. The median age was 62 years old (34–85), 64% of patients were female and 58% of these females had breast cancer. In the population, self-reported pain was 91.6%, with 29 patients (34.5%) reporting severe pain (score 7–10). Among these patients, only 13 (44.8%) presented a similar report to that of their clinical files and 5 were undergoing treatment with strong opioids (17.2%). A total of 45 patients (46%) had not been prescribed analgesic drugs, of these patients, 32 were treated with a weak opioid, and 13 with a strong opioid. An association was observed between pain records and the prescribed analgesic (P=0.031). BPI maximum pain and overall survival data were analyzed, and a significant association was identified between male patients presenting severe pain and decreased survival (P=0.004). Male survival was associated with severe pain, which is consistent with other data. The results revealed a skeletal-related events (SRE)-free survival (time elapsed from diagnosis of the first bone metastasis to the first SRE) of 9 months (4.39–13.73, 95% CI) with a statistically significant difference between subgroups of time since diagnosis of bone metastasis (P=0.005). The added value of the present study is the suggestion that complete and accurate pain narratives are mandatory and may contribute to the optimization of analgesia, and may help to increase survival rates. Optimal pain management for patients with cancer remains an urgent requirement.