Predicting prostate cancer progression: protocol for a retrospective cohort study to identify prognostic factors for prostate cancer outcomes using routine primary care data

Survival Rate and Prognostic Factors of Localised Prostate Cancer in Southeast Asian Countries: A Systematic Review with Meta-Analysis

Prostate cancer (Pca) is one of the most prevalent health conditions affecting men, particularly older men, and cases have increased in recent years.

OBJECTIVE

This review examined the survival rate and prognostic factors of patients with Pca in Southeast Asia (SEA).

METHODS

We conducted a systematic search of three databases (PubMed, Scopus, Web of Science) and a manual search until April 1, 2022. The selected papers were evaluated using the Newcastle-Ottawa Quality Assessment Form for Cohort Studies. The review protocol was registered with PROSPERO (CRD42022326521). Pooled prevalence rates were calculated using the programme R version 4.2.1. Heterogeneity was assessed using the I2 statistic and p-value. A narrative approach was used to describe prognostic factors. Studies were selected and finalised based on the review question. The quality of the included studies was assessed.

RESULTS

A total of 11 studies were included in this review. The 1-, 3-, 5- and 10-year survival rates of SEA Pca cases were 80.8%, 51.9%, 66.1% (range 32.1-100) and 78% (range 55.9-100), respectively. Prognostic factors for Pca were discussed in terms of sociodemographic, disease-related and treatment-related aspects. The predictors of significantly lower survival were age more than 75 years, cancer detected during transurethral resection of the prostate, Gleason score more or equal to eight, high-risk group, metastases and no adjuvant radiotherapy. A meta-analysis on the pooled HR of prostate cancer could not be performed due to the heterogeneity of prognostic factors. The pooled prevalence of localised and metastatic prostate cancer in SEA countries was 39% 95% CI [20-62] and 40% 95% CI [28-53], respectively.

CONCLUSION

The survival rate in SEA countries can be determined by prognostic factors, which can be divided into sociodemographic, disease-related and treatment-related factors. Therefore, further studies are needed to improve the understanding and treatment of Pca in the region SEA.

A multicentre randomised controlled trial of a guided self-help cognitive behavioural therapy to MANage the impact of hot flushes and night sweats in patients with prostate CANcer undergoing androgen deprivation therapy (MANCAN2)

BACKGROUND

Androgen deprivation therapy (ADT) is prescribed to almost half of all men diagnosed with prostate cancer. Although ADT is effective treatment, with virtually all men with advanced disease showing initial clinical response, it is associated with troublesome side effects including hot flushes and night sweats (HFNS). HFNS can be both frequent and severe and can have a significant impact on quality of life (QoL). They can occasionally be so debilitating that patients stop ADT altogether, despite the increased risk of disease relapse or death. Previous research has found that guided self-help cognitive behavioural therapy (CBT) can be effective in reducing HFNS due to ADT when delivered by a clinical psychologist. MANCAN2 aims test whether we can train the existing NHS Prostate Cancer Nurse Specialist (CNS) team to deliver guided self-help CBT and whether it is effective in reducing the impact of HFNS in men undergoing ADT.

METHODS

MANCAN2 is a phase III multicentre randomised controlled trial and process evaluation. Between 144 and 196 men with prostate cancer who are currently receiving ADT and are experiencing problematic HFNS will be individually randomised in a 1:1 ratio in groups of 6-8 participants to either treatment as usual (TAU) or participation in the guided self-help CBT intervention plus TAU. A process evaluation using the normalisation process theory (NPT) framework will be conducted, to understand the CNS team's experiences of delivering the intervention and to establish the key influencers to its implementation as a routine practice service. Fidelity of implementation of the intervention will be conducted by expert assessment. The cost-effectiveness of the intervention and participant adherence to the trial intervention will also be assessed.

DISCUSSION

MANCAN2 will advance the program of work already conducted in development of management strategies for HFNS. This research will determine whether the severity of ADT-induced HFNS in men with prostate cancer can be reduced by a guided self-help CBT intervention, delivered by the existing NHS prostate cancer CNS team, within a multicentre study. The emphasis on this existing team, if successful, should facilitate translation through to implementation in routine practice.

TRIAL REGISTRATION

ISRCTN reference 58720120 . Registered 13 December 2022.

Identifying persistent somatic symptoms in electronic health records: exploring multiple theory-driven methods of identification

OBJECTIVE

Persistent somatic symptoms (PSSs) are defined as symptoms not fully explained by well-established pathophysiological mechanisms and are prevalent in up to 10% of patients in primary care. The present study aimed to explore methods to identify patients with a recognisable risk of having PSS in routine primary care data.

DESIGN

A cross-sectional study to explore four identification methods that each cover part of the broad spectrum of PSS was performed. Cases were selected based on (1) PSS-related syndrome codes, (2) PSS-related symptom codes, (3) PSS-related terminology and (4) Four-Dimensional Symptom Questionnaire scores and all methods combined.

SETTING

Coded electronic health record data were extracted from 76 general practices in the Netherlands.

PARTICIPANTS

Patients who were registered for at least 1 year during 2014-2018, were included (n=169 138).

OUTCOME MEASURES

Identification methods were explored based on (1) PSS sample sizes and demographics, (2) presence of chronic conditions and (3) healthcare utilisation (HCU) variables. Overlap between methods and practice specific differences were examined.

RESULTS

The percentage of cases identified varied between 0.3% and 7.0% across the methods. Over 58.1% of cases had chronic physical condition(s) and over 33.8% had chronic mental condition(s). HCU was generally higher for cases selected by any method compared with the total cohort. HCU was higher for method B compared with the other methods. In 26.7% of cases, cases were selected by multiple methods. Overlap between methods was low.

CONCLUSIONS

Different methods yielded different patient samples which were general practice specific. Therefore, for the most comprehensive data-based selection of PSS cases, a combination of methods A, C and D would be recommended. Advanced (data-driven) methods are needed to create a more sensitive algorithm for identifying the full spectrum of PSS. For clinical purposes, method B could possibly support screening of patients who are currently missed in daily practice.

Retrospective cohort study evaluating clinical, biochemical and pharmacological prognostic factors for prostate cancer progression using primary care data

OBJECTIVES

To confirm the association of previously reported prognostic factors with future progression of localised prostate cancer using primary care data and identify new potential prognostic factors for further assessment in prognostic model development and validation.

DESIGN

Retrospective cohort study, employing Cox proportional hazards regression controlling for age, prostate specific antigen (PSA), and Gleason score, was stratified by diagnostic stage.

SETTING

Primary care in England.

PARTICIPANTS

Males with localised prostate cancer diagnosedbetween 01/01/1987 and 31/12/2016 within the Clinical Practice ResearchDatalink database, with linked data from the National Cancer Registration andAnalysis Service and Office for National Statistics.

PRIMARY AND SECONDARY OUTCOMES

Primary outcome measure was prostate cancer mortality. Secondary outcome measures were all-cause mortality and commencing systemic therapy. Up-staging after diagnosis was not used as a secondary outcome owing to significant missing data.

RESULTS

10 901 men (mean age 74.38±9.03 years) with localised prostate cancer were followed up for a mean of 14.12 (±6.36) years. 2331 (21.38%) men underwent systemic therapy and 3450 (31.65%) died, including 1250 (11.47%) from prostate cancer. Factors associated with an increased risk of prostate cancer mortality included age; high PSA; current or ex-smoker; ischaemic heart disease; high C reactive protein; high ferritin; low haemoglobin; high blood glucose and low albumin.

CONCLUSIONS

This study identified several new potential prognostic factors for prostate cancer progression, as well as confirming some known prognostic factors, in an independent primary care data set. Further research is needed to develop and validate a prognostic model for prostate cancer progression.

Health-Related Quality of Life and Survival in Prostate Cancer Patients in a Real-World Setting

OBJECTIVE

To analyze the health-related quality of life (HRQoL) and survival of real-world prostate cancer (PC) patients and to calculate quality-adjusted life-years (QALYs) experienced under different treatment strategies.

MATERIALS AND METHODS

PC patients undergoing active surveillance (n = 226), radiation treatment (n = 280), surgery (n = 299), or hormonal treatment (n = 62) responded to the generic 15-dimensional (15D) HRQoL questionnaire at the time of the diagnosis and were followed up 3, 6, 12, and 24 months later. QALYs experienced during the follow-up were calculated for each treatment group, and variables associated with survival were analyzed using Cox proportional hazards models.

RESULTS

HRQoL was stable during the first 2 years after diagnosis in all other treatment groups, except in patients treated with hormonal therapy. The overall survival within 6.5-year follow-up time was 84.4%. The number of QALYs experienced during the 2-year follow-up was similar in patients in active surveillance (1.790), surgery (1.784), and radiation groups (1.767), but significantly lower in the hormonal therapy group (1.665).

CONCLUSIONS

Patients receiving hormonal treatment had significantly impaired HRQoL and survival compared with other treatments. Although the number of QALYs experienced was similar in the 3 other treatment lines, there were marked differences between treatment lines on some 15D dimensions.

X-ray tomography of cryopreserved human prostate cancer cells: mitochondrial targeting by an organoiridium photosensitiser

Abstract

The organoiridium complex Ir[(C,N)₂(O,O)] (1) where C, N = 1-phenylisoquinoline and O,O = 2,2,6,6-tetramethyl-3,5-heptanedionate is a promising photosensitiser for Photo-Dynamic Therapy (PDT). 1 is not toxic to cells in the dark. However, irradiation of the compound with one-photon blue or two-photon red light generates high levels of singlet oxygen (¹O₂) (in Zhang et al. Angew Chem Int Ed Engl 56 (47):14898-14902 10.1002/anie.201709082,2017), both within cell monolayers and in tumour models. Moreover, photo-excited 1 oxidises key proteins, causing metabolic alterations in cancer cells with potent antiproliferative activity. Here, the tomograms obtained by cryo-Soft X-ray Tomography (cryo-SXT) of human PC3 prostate cancer cells treated with 1, irradiated with blue light, and cryopreserved to maintain them in their native state, reveal that irradiation causes extensive and specific alterations to mitochondria, but not other cellular components. Such new insights into the effect of ¹O₂ generation during PDT using iridium photosensitisers on cells contribute to a detailed understanding of their cellular mode of action.

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s00775-020-01761-8) contains supplementary material, which is available to authorized users.

Cohort profile: the MCC-Spain follow-up on colorectal, breast and prostate cancers: study design and initial results

PURPOSE

Since 2016, the multicase-control study in Spain (MCC-Spain) has focused towards the identification of factors associated with cancer prognosis. Inception cohorts of patients with colorectal, breast and prostate cancers were assembled using the incident cases originally recruited.

PARTICIPANTS

2140 new cases of colorectal cancer, 1732 of breast cancer and 1112 of prostate cancer were initially recruited in 12 Spanish provinces; all cancers were incident and pathologically confirmed. Follow-up was obtained for 2097 (98%), 1685 (97%) and 1055 (94.9%) patients, respectively.

FINDINGS TO DATE

Information gathered at recruitment included sociodemographic factors, medical history, lifestyle and environmental exposures. Biological samples were obtained, and 80% of patients were genotyped using a commercial exome array. The follow-up was performed by (1) reviewing medical records; (2) interviewing the patients by phone on quality of life; and (3) verifying vital status and cause of death in the Spanish National Death Index. Ninety-seven per cent of recruited patients were successfully followed up in 2017 or 2018; patient-years of follow-up were 30 914. Most colorectal cancers (52%) were at clinical stage II or lower at recruitment; 819 patients died in the follow-up and the 5-year survival was better for women (74.4%) than men (70.0%). 71% of breast cancers were diagnosed at stages I or II; 206 women with breast cancer died in the follow-up and the 5-year survival was 90.7%. 49% of prostate cancers were diagnosed at stage II and 32% at stage III; 119 patients with prostate cancer died in the follow-up and the 5-year survival was 93.7%.

FUTURE PLANS

MCC-Spain has built three prospective cohorts on highly frequent cancers across Spain, allowing to investigate socioeconomic, clinical, lifestyle, environmental and genetic variables as putative prognosis factors determining survival of patients of the three cancers and the inter-relationship of these factors.

Stein-type shrinkage estimators in gamma regression model with application to prostate cancer data

Gamma regression is applied in several areas such as life testing, forecasting cancer incidences, genomics, rainfall prediction, experimental designs, and quality control. Gamma regression models allow for a monotone and no constant hazard in survival models. Owing to the broad applicability of gamma regression, we propose some novel and improved methods to estimate the coefficients of gamma regression model. We combine the unrestricted maximum likelihood (ML) estimators and the estimators that are restricted by linear hypothesis, and we present Stein-type shrinkage estimators (SEs). We then develop an asymptotic theory for SEs and obtain their asymptotic quadratic risks. In addition, we conduct Monte Carlo simulations to study the performance of the estimators in terms of their simulated relative efficiencies. It is evident from our studies that the proposed SEs outperform the usual ML estimators. Furthermore, some tabular and graphical representations are given as proofs of our assertions. This study is finally ended by appraising the performance of our estimators for a real prostate cancer data.

India and the United Kingdom-What big data health research can do for a country

INTRODUCTION

Big data and growth in telecommunications have increased the enormous promise of an informatics approach to health care. India and the United Kingdom are two countries facing these challenges of implementing learning health systems and big data health research.

ANALYSIS

At present, these opportunities are more likely to be exploited in the private sector or in public-private partnerships (eg, Public Health Foundation of India [PHFI]) than public sector ventures alone. In both India and the United Kingdom, the importance of health informatics (HIs), a relatively new discipline, is being recognised and there are national initiatives in academic and health sectors to fill gaps in big data health research. The challenges are in many ways greater in India but outweighed by three potential benefits in health-related scientific research: (a) increased productivity; (b) a learning health system with better use of data and better health outcomes; and (c) to fill workforce gaps in both research and practice.

CONCLUSIONS

Despite several system-level obstacles, in India, big data research in health care can improve the status quo, whether in terms of patient outcomes or scientific discovery. Collaboration between India and the United Kingdom in HI can result in mutual benefits to academic and health care delivery organisations in both countries and can serve as examples to other countries embracing the promises and the pitfalls of health care research in the digital era.