An appraisal of analytical tools used in predicting clinical outcomes following radiation therapy treatment of men with prostate cancer: a systematic review

EviGUIDE - a tool for evidence-based decision making in image-guided adaptive brachytherapy for cervical cancer

PURPOSE

To develop a novel decision-support system for radiation oncology that incorporates clinical, treatment and outcome data, as well as outcome models from a large clinical trial on magnetic resonance image-guided adaptive brachytherapy (MR-IGABT) for locally advanced cervical cancer (LACC).

METHODS

A system, called EviGUIDE, was developed that combines dosimetric information from the treatment planning system, patient and treatment characteristics, and established tumor control probability (TCP), and normal tissue complication probability (NTCP) models, to predict clinical outcome of radiotherapy treatment of LACC. Six Cox Proportional Hazards models based on data from 1341 patients of the EMBRACE-I study have been integrated. One TCP model for local tumor control, and five NTCP models for OAR morbidities.

RESULTS

EviGUIDE incorporates TCP-NTCP graphs to help users visualize the clinical impact of different treatment plans and provides feedback on achievable doses based on a large reference population. It enables holistic assessment of the interplay between multiple clinical endpoints and tumour and treatment variables. Retrospective analysis of 45 patients treated with MR-IGABT showed that there exists a sub-cohort of patients (20%) with increased risk factors, that could greatly benefit from the quantitative and visual feedback.

CONCLUSION

A novel digital concept was developed that can enhance clinical decision- making and facilitate personalized treatment. It serves as a proof of concept for a new generation of decision support systems in radiation oncology, which incorporate outcome models and high-quality reference data, and aids the dissemination of evidence-based knowledge about optimal treatment and serve as a blueprint for other sites in radiation oncology.

Progress in the study of molecular mechanisms of cell pyroptosis in tumor therapy

Pyroptosis, also known as cellular inflammatory necrosis, is a programmed cell death mediated by the Gasdermin family of proteins. The mechanisms by which pyroptosis occurs are divided into the GSDMD-mediated Caspase-1 and Caspase-4/-5/-11-dependent classical inflammatory vesicle pathway and the GSDME-mediated Caspase-3 and granzyme-dependent non-classical inflammatory vesicle pathways, among others. Recent studies have shown that pyroptosis has both inhibitory and promotive effects on tumor development. Pyroptosis induction also plays a dual role in antitumor immunotherapy: on the one hand, it suppresses antitumor immunity by promoting the release of inflammatory factors, and on the other hand, it inhibits tumor cell proliferation by triggering antitumor inflammatory responses. In addition, cell scorching plays an essential role in chemotherapy. It has been found that natural drugs modulating the induction of cell scorch are necessary to treat tumors. Therefore, studying the specific mechanisms of cell pyroptosis in different tumors can provide more ideas for developing oncology drugs. In this paper, we review the molecular mechanisms of pyroptosis and the role of pyroptosis in tumor development and treatment to provide new targets for clinical tumor treatment, prognosis, and antitumor drug development.

YB-1: The key to personalised prostate cancer management?

Y-box-binding protein 1 (YB-1) is a DNA/RNA binding protein increasingly implicated in the regulation of cancer cell biology. Normally located in the cytoplasm, nuclear localisation in prostate cancer is associated with more aggressive, potentially treatment-resistant disease. This is attributed to the ability of YB-1 to act as a transcription factor for various target genes associated with androgen receptor signalling, survival, DNA repair, proliferation, invasion, differentiation, angiogenesis and hypoxia. This review aims to examine the clinical potential of YB-1 in the detection and therapeutic management of prostate cancer.

Models predicting survival to guide treatment decision-making in newly diagnosed primary non-metastatic prostate cancer: a systematic review

OBJECTIVES

Men diagnosed with non-metastatic prostate cancer require standardised and robust long-term prognostic information to help them decide on management. Most currently-used tools use short-term and surrogate outcomes. We explored the evidence base in the literature on available pre-treatment, prognostic models built around long-term survival and assess the accuracy, generalisability and clinical availability of these models.

DESIGN

Systematic literature review, pre-specified and registered on PROSPERO (CRD42018086394).

DATA SOURCES

MEDLINE, Embase and The Cochrane Library were searched from January 2000 through February 2018, using previously-tested search terms.

ELIGIBILITY CRITERIA

Inclusion required a multivariable model prognostic model for non-metastatic prostate cancer, using long-term survival data (defined as ≥5 years), which was not treatment-specific and usable at the point of diagnosis.

DATA EXTRACTION AND SYNTHESIS

Title, abstract and full-text screening were sequentially performed by three reviewers. Data extraction was performed for items in the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Individual studies were assessed using the new Prediction model Risk Of Bias ASsessment Tool.

RESULTS

Database searches yielded 6581 studies after deduplication. Twelve studies were included in the final review. Nine were model development studies using data from over 231 888 men. However, only six of the nine studies included any conservatively managed cases and only three of the nine included treatment as a predictor variable. Every included study had at least one parameter for which there was high risk of bias, with failure to report accuracy, and inadequate reporting of missing data common failings. Three external validation studies were included, reporting two available models: The University of California San Francisco (UCSF) Cancer of the Prostate Risk Assessment score and the Cambridge Prognostic Groups. Neither included treatment effect, and both had potential flaws in design, but represent the most robust and usable prognostic models currently available.

CONCLUSION

Few long-term prognostic models exist to inform decision-making at diagnosis of non-metastatic prostate cancer. Improved models are required to inform management and avoid undertreatment and overtreatment of non-metastatic prostate cancer.

Systematic review of clinical prediction models for survival after surgery for resectable pancreatic cancer

BACKGROUND

As more therapeutic options for pancreatic cancer are becoming available, there is a need to improve outcome prediction to support shared decision-making. A systematic evaluation of prediction models in resectable pancreatic cancer is lacking.

METHODS

This systematic review followed the CHARMS and PRISMA guidelines. PubMed, Embase and Cochrane Library databases were searched up to 11 October 2017. Studies reporting development or validation of models predicting survival in resectable pancreatic cancer were included. Models without performance measures, reviews, abstracts or more than 10 per cent of patients not undergoing resection in postoperative models were excluded. Studies were appraised critically.

RESULTS

After screening 4403 studies, 22 (44 319 patients) were included. There were 19 model development/update studies and three validation studies, altogether concerning 21 individual models. Two studies were deemed at low risk of bias. Eight models were developed for the preoperative setting and 13 for the postoperative setting. Most frequently included parameters were differentiation grade (11 of 21 models), nodal status (8 of 21) and serum albumin (7 of 21). Treatment-related variables were included in three models. The C-statistic/area under the curve values ranged from 0·57 to 0·90. Based on study design, validation methods and the availability of web-based calculators, two models were identified as the most promising.

CONCLUSION

Although a large number of prediction models for resectable pancreatic cancer have been reported, most are at high risk of bias and have not been validated externally. This overview of prognostic factors provided practical recommendations that could help in designing easily applicable prediction models to support shared decision-making.

Prognostic models for predicting overall survival in metastatic castration-resistant prostate cancer: a systematic review

PURPOSE

Prognostic models are developed to estimate the probability of the occurrence of future outcomes incorporating multiple variables. We aimed to identify and summarize existing multivariable prognostic models developed for predicting overall survival in patients with metastatic castration-resistant prostate cancer (mCRPC).

METHODS

The protocol was prospectively registered (CRD42017064448). We systematically searched Medline and reference lists up to May 2018 and included experimental and observational studies, which developed and/or internally validated prognostic models for mCRPC patients and were further externally validated or updated. The outcome of interest was overall survival. Two authors independently performed literature screening and quality assessment.

RESULTS

We included 12 studies that developed models including 8750 patients aged 42-95 years. Models included 4-11 predictor variables, mostly hemoglobin, baseline PSA, alkaline phosphatase, performance status, and lactate dehydrogenase. Very few incorporated Gleason score. Two models included predictors related to docetaxel and mitoxantrone treatments. Model performance after internal validation showed similar discrimination power ranging from 0.62 to 0.73. Overall survival models were mainly constructed as nomograms or risk groups/score. Two models obtained an overall judgment of low risk of bias.

CONCLUSIONS

Most models were not suitable for clinical use due to methodological shortcomings and lack of external validation. Further external validation and/or model updating is required to increase prognostic accuracy and clinical applicability prior to their incorporation in clinical practice as a useful tool in patient management.

Qianlie Xiaozheng Decoction Induces Autophagy in Human Prostate Cancer Cells via Inhibition of the Akt/mTOR Pathway

Qianlie Xiaozheng decoction (QLXZD), a traditional Chinese medicinal formula, has been used clinically to treat advanced prostate cancer (PCa) for more than 10 years. However, experimental evidence supporting its efficacy is lacking. Here, we investigated the anticancer properties and molecular mechanism of QLXZD in vitro in a human PCa cell line (PC3) and in vivo using PC3 xenografts in nude mice. We confirmed the antineoplastic activity of QLXZD by analyzing cell viability and tumor volume growth, which decreased significantly compared to that of the controls. Autophagy following QLXZD treatment was detected morphologically using transmission electron microscopy and was confirmed by measuring the expression of autophagy markers (LC3-II and p62) using fluorescence analysis, flow cytometry, and western blotting. Increasing autophagic flux induced by QLXZD was monitored via pmCherry-GFP-LC3 fluorescence analysis. QLXZD-induced autophagic cell death was alleviated by the autophagy inhibitors, 3-methyl adenine and hydroxychloroquine. We evaluated the total expression and phosphorylation levels of proteins involved in the Akt/mTOR pathway regulating autophagy. Phosphorylation of Akt, mTOR, and p70S6K, but not total protein levels, decreased following treatment. This is the first study to demonstrate the autophagy-related mechanistic pathways utilized during QLXZD-mediated antitumor activity both in vitro and in vivo. These findings support the clinical use of QLXZD for PCa treatment.

Prognostic and predictive factors in patients with brain metastases from solid tumors: A review of published nomograms

OBJECTIVE

To review published nomograms that predict endpoints such as overall survival (OS) or risk of intracranial relapse in patients with brain metastases from solid tumors.

METHODS

The methods and results of nomogram studies identified by a systematic search were extracted and compared, stratified by endpoint predicted by the respective nomograms. In particular, validation strategies (external/internal), concordance indices (cut-off 0.75) and comparisons to older models were analyzed.

RESULTS

Six publications reported on prediction of OS. Most of these analyses focused on one particular primary tumor site, e.g., breast cancer or hepatocellular carcinoma, while the largest study included different primary tumor sites. The median number of patients was 244. Three of six studies included external validation cohorts. With few exceptions, concordance indices <0.75 were reported. In all studies reporting this endpoint, the nomogram outperformed older prognostic scores. Two nomograms focused on development of new brain metastases after radiosurgery (one externally validated), one on survival free from salvage whole brain radiotherapy (WBRT) after radiosurgery, and one on neurologic and non-neurologic death in patients receiving radiosurgery after WBRT failure. All concordance indices of these 4 nomograms were <0.70.

CONCLUSION

Taking into account concordance indices and comparisons to older prognostic models, the most promising, externally validated nomograms are the breast cancer and the non-small cell lung cancer nomogram predicting OS, and the distant brain failure after radiosurgery nomogram. Additional validation studies as well as continuous monitoring of the models' performance appear necessary to ensure their clinical applicability in the present era of rapidly changing treatment paradigms.

Tools for Predicting Clinical and Patient-reported Outcomes in Prostate Cancer Patients Undergoing Androgen Deprivation Therapy: A Systematic Review of Prognostic Accuracy and Validity

Androgen deprivation therapy (ADT) can result in a range of adverse symptoms that reduce patients' quality of life. Careful patient counseling on the likely clinical outcomes and adverse effects is therefore vital. The present systematic review was undertaken to identify and characterize all the tools used for the prediction of clinical and patient-reported outcome measures (PROMs) in patients with prostate cancer undergoing ADT. PubMed and EMBASE were systematically searched from 2007 to 2016. Search terms related to the inclusion criteria were: prostate cancer, clinical outcomes, PROMs, ADT, and prognosis. Titles and abstracts were reviewed to find relevant studies, which were advanced to full-text review. The reference lists were screened for additional studies. The Centre for Evidence Based Medicine critical appraisal of prognostic studies tool was applied. The search strategy identified 8755 studies. Of the 8755 studies, 22 on clinical outcomes were identified. However, no studies of PROMs were found. Nine tools could be used to predict clinical outcomes in treatment-naive patients and 10 in patients with recurrence. The Japan Cancer of the Prostate Risk Assessment (J-CAPRA) nomogram was the best performing and validated tool for the prediction of clinical outcomes in treatment-naive patients, and the Chi and Shamash prognostic indexes have been validated for use in patients with castration-resistant disease in different clinical contexts. Using the J-CAPRA nomogram should help clinicians deliver accurate, evidence-based counseling to patients undergoing primary ADT. A strong need exists for primary studies that derive and validate tools for the prediction of PROMs in patients undergoing ADT under any circumstance because these are currently absent from the literature.