Incorporating multiparametric MRI staging and the new histological Grade Group system improves risk-stratified detection of bone metastasis in prostate cancer

Are staging bone scans necessary in patients with T3a prostate cancer? A multicentre study

Objective:

Studies reporting increased risk of metastases in T3a disease are based on clinical staging (Digital rectal examination) in the pre-multiparametric–magnetic resonance imaging (MRI) (mp-MRI) era. The aim of our study was to assess the rate of positive bone scans in patients ascribed with T3a prostate cancer on a pre-biopsy mp-MRI.

Methods:

We performed a multicentre, retrospective analysis of all patients with T3a prostate cancer staged by mp-MRI who had a bone scan between January 2017 and April 2020.

Results:

A total of 586 patients were diagnosed with T3a prostate cancer on mp-MRI, with a median age of 71 years (range: 47–87). The median presenting PSA was 11 ng/mL (range: 1–537); 125 patients (21.3%) had a PSA ⩽ 20 and either grade group (GG) 1 or 2 in their prostate biopsy; none of these patients had bone metastases. Eighteen patients (3.1%) were found to have bone metastases: 11 patients had GG ⩾ 3 disease on biopsy and nodal disease, 6 had GG ⩾ 3 without evidence of nodal disease and 1 had a PSA of 103.

Conclusion:

The use of bone scans in patients with T3a prostate cancer staged on mp-MRI but without other evidence of high-risk disease (GG ⩾ 3 and PSA > 20 ng/mL) appears to be unnecessary and could be safely avoided.

Level of evidence:

2b

Rates of Positive Abdominal Computed Tomography and Bone Scan Findings Among Men with Cambridge Prognostic Group 4 or 5 prostate cancer: A Nationwide Registry Study

European and American guidelines recommend abdominal computed tomography (CT) and bone scans for staging of high-risk prostate cancer (PC). To improve clinical risk stratification of nonmetastatic PC a new, five-tier risk classification system has been developed, the Cambridge Prognostic Groups (CPG), in which "high-risk" PC is divided into favourable CPG 4 and unfavourable CPG 5. We used the National Prostate Cancer Register of Sweden (NPCR) to define the rates of positive CT and bone scan findings among men with CPG 4 or 5 cancer. Among men with CPG 4 and prostate-specific antigen (PSA) <50 ng/ml, only 3.6% (95% confidence interval 2.9-4.5%) of the CT scans showed regional lymph-node metastasis (N1M0), while 6.2% (95% confidence interval 5.4-7.0%) of the bone scans were positive. Rates for both were higher in the subgroups with PSA 50-99 ng/ml (10% and 15%) and with CPG 5 disease. The low positivity rate questions routine use of CT for men with CPG 4 cancer and PSA <50 ng/ml, particularly considering the poor sensitivity and specificity for detection of lymph node metastasis. The positivity rate was higher for bone scans, and as current clinical practice relies on trials using bone scans for staging (eg, to define low- versus high-volume metastatic disease), continued routine use of bone scans seems justified.

Patient summary

Our analysis of data from the National Prostate Cancer Register of Sweden showed that for men with favourable high-risk prostate cancer (Cambridge Prognostic Group 4), the rate of positive computed tomography (CT) scans was low. This result suggests that CT scans may not be necessary for detecting cancer spread in men with Cambridge Prognostic Group 4 prostate cancer .

Evaluation of selective bone scan staging in prostate cancer - external validation of current strategies and decision-curve analysis

Background

Recommendations for staging newly diagnosed prostate cancer patients vary between guidelines and literature.

Methods

Our objective was to validate and compare prediction models selecting newly diagnosed prostate cancer patients for bone scan staging. To achieve this, we validated eleven models in a population-based cohort of 10,721 patients diagnosed with prostate cancer between 2005 and 2019. The primary outcome was net-benefit. This was assessed at different balances of conservatism and tolerance, represented by preference ratio and number-willing-to-test (NWT). Secondary outcomes included calibration slope, calibration-in-the-large (intercept), and discrimination measured by Area-under-the-receiver-operator-characteristics curve (AUC).

Results

For preference ratios less than 1:39 (NWT greater than 40), scanning everyone provided greater net-benefit than selective staging. For preference ratios 1:39 to 3:97 (NWT 33–40), the European Association of Urology (EAU) 2020 guideline recommendation was the best approach. For preference ratios 3:97–7:93 (NWT 14–33), scanning EAU high-risk patients only was preferable. For preference ratios 7:93–1:9 (NWT 10–13), scanning only Gnanapragasam Group 5 patients was best. All models had similar fair discrimination (AUCs 0.68–0.80), but most had poor calibration.

Conclusions

We identified three selective staging strategies that outperformed all other approaches but did so over different ranges of conservatism and tolerance. Scanning only EAU high-risk patients provided the greatest net-benefit over the greatest range of preference ratios and scenarios, but other options may be preferable depending upon the local healthcare system’s degree of conservatism and tolerance.

A Radiomics nomogram for predicting bone metastasis in newly diagnosed prostate cancer patients

PURPOSE

To establish and validate a radiomics nomogram for predicting bone metastasis (BM) in patients with newly diagnosed prostate cancer (PCa).

METHOD

One-hundred and sixteen patients (training cohort: n = 81; validation cohort: n = 35) who underwent prostate MR imaging and confirmed by pathology with newly diagnosed PCa from January 2014 to January 2019 were enrolled. Radiomic features were extracted from diffusion-weighted, axial T2-weighted fat suppression, and dynamic contrast-enhanced T1-weighted MRI of each patient. Dimension reduction, feature selection, and radiomics feature construction were performed using the least absolute shrinkage and selection operator (LASSO) regression. Combined with independent clinical risk factors, a multivariate logistic regression model was used to establish a radiomics nomogram. Nomogram calibration and discrimination were evaluated in training cohort and verified in the validation cohort. Finally, the clinical usefulness of the nomogram was estimated through decision curve analysis (DCA).

RESULTS

Radiomics signature consisting of 12 selected features was significantly correlated with bone status (P < 0.001 for both training and validation sets). The radiomics nomogram combined a radiomics signature from multiparametric MR images with independent clinic risk factors. The model showed good discrimination and calibration in the training cohort (AUC 0.93, 95% CI, 0.86 to 0.99) and the validation cohort (AUC 0.92, 95% CI, 0.84 to 0.99). DCA also demonstrated the clinical use of the radiomics model.

CONCLUSION

The radiomics nomogram, which incorporates the multiparametric MRI-based radiomics signature and clinical risk factors, can be conveniently used to promote individualized prediction of BM in patients with newly diagnosed PCa.

Using prognosis to guide inclusion criteria, define standardised endpoints and stratify follow-up in active surveillance for prostate cancer

OBJECTIVES

To test whether using disease prognosis can inform a rational approach to active surveillance (AS) for early prostate cancer.

PATIENTS AND METHODS

We previously developed the Cambridge Prognostics Groups (CPG) classification, a five-tiered model that uses prostate-specific antigen (PSA), Grade Group and Stage to predict cancer survival outcomes. We applied the CPG model to a UK and a Swedish prostate cancer cohort to test differences in prostate cancer mortality (PCM) in men managed conservatively or by upfront treatment in CPG2 and 3 (which subdivides the intermediate-risk classification) vs CPG1 (low-risk). We then applied the CPG model to a contemporary UK AS cohort, which was optimally characterised at baseline for disease burden, to identify predictors of true prognostic progression. Results were re-tested in an external AS cohort from Spain.

RESULTS

In a UK cohort (n = 3659) the 10-year PCM was 2.3% in CPG1, 1.5%/3.5% in treated/untreated CPG2, and 1.9%/8.6% in treated/untreated CPG3. In the Swedish cohort (n = 27 942) the10-year PCM was 1.0% in CPG1, 2.2%/2.7% in treated/untreated CPG2, and 6.1%/12.5% in treated/untreated CPG3. We then tested using progression to CPG3 as a hard endpoint in a modern AS cohort (n = 133). During follow-up (median 3.5 years) only 6% (eight of 133) progressed to CPG3. Predictors of progression were a PSA density ≥0.15 ng/mL/mL and CPG2 at diagnosis. Progression occurred in 1%, 8% and 21% of men with neither factor, only one, or both, respectively. In an independent Spanish AS cohort (n = 143) the corresponding rates were 3%, 10% and 14%, respectively.

CONCLUSION

Using disease prognosis allows a rational approach to inclusion criteria, discontinuation triggers and risk-stratified management in AS.

The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study

BACKGROUND

The purpose of this study is to validate a new five-tiered prognostic classification system to better discriminate cancer-specific mortality in men diagnosed with primary non-metastatic prostate cancer.

METHODS

We applied a recently described five-strata model, the Cambridge Prognostic Groups (CPGs 1-5), in two international cohorts and tested prognostic performance against the current standard three-strata classification of low-, intermediate- or high-risk disease. Diagnostic clinico-pathological data for men obtained from the Prostate Cancer data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality.

RESULTS

The PCBaSe cohort included 72,337 men, of whom 7162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk regression confirming significant intergroup distinction (p < 0.0001). The CPGs were significantly better at stratified prediction of PCM compared to the current three-tiered system (concordance index (C-index) 0.81 vs. 0.77, p < 0.0001). This superiority was maintained for every age group division (p < 0.0001). Also in the ethnically different Singapore cohort of 2550 men with 142 prostate cancer deaths, the CPG model outperformed the three strata categories (C-index 0.79 vs. 0.76, p < 0.0001). The model also retained superior prognostic discrimination in the treatment sub-groups: radical prostatectomy (n = 20,586), C-index 0.77 vs. 074; radiotherapy (n = 11,872), C-index 0.73 vs. 0.69; and conservative management (n = 14,950), C-index 0.74 vs. 0.73. The CPG groups that sub-divided the old intermediate-risk (CPG2 vs. CPG3) and high-risk categories (CPG4 vs. CPG5) significantly discriminated PCM outcomes after radical therapy or conservative management (p < 0.0001).

CONCLUSIONS

This validation study of nearly 75,000 men confirms that the CPG five-tiered prognostic model has superior discrimination compared to the three-tiered model in predicting prostate cancer death across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes. We therefore propose adoption of the CPG model as a simple-to-use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer.

Prostate cancer grading: a decade after the 2005 modified system

This review article will cover the evolution of grading of prostate cancer from the original Gleason system in the 1960-1970s to a more patient-centric grading system proposed in 2013 from a group at Johns Hopkins Hospital, validated in 2014 by a large multi-institutional study, and subsequently accepted by the World Health Organization (WHO), College of American Pathology (CAP), and the AJCC TNM system. Covered topics include: (1) historical background; (2) 2005 and 2014 International Society of Urological Pathology Grading Conferences; (3) Description of Gleason patterns; (4) new approaches to display Gleason grades; (5) grading variants and variations of acinar adenocarcinoma; (6) reporting rules for Gleason grading reporting secondary patterns of higher grade when present to a limited extent; (7) reporting secondary patterns of lower grade when present to a limited extent; (8) reporting percentage pattern 4; (9) general applications of the Gleason grading system; (10) needle biopsy with different cores showing different grades; (11) radical prostatectomy specimens with separate tumor nodules; and (12) a new grading system for prostate cancer.

Novel three-dimensional bone 'mapping' software can help assess progression of osseous metastases from routine CT

Imaging of bone metastasis response to therapy is a research priority. Stradwin is a new software-tool, with demonstrated sub-voxel accuracy in assessing cortical bone properties from routine CT. We applied this technology to the context of osseous metastases, with particular focus on disease progression using prostate cancer as a model. 3D-rendered 'bone-maps' were produced for 20 men with advanced prostate cancer, including a sub-cohort of 9 who had undergone serial scans. Correlation between baseline interpretation and assessments of progression between modalities was assessed. Bone-maps took significantly less time to interpret than CT bone windows (P < 0.001). Initial bone-mapping, without adjustment, demonstrated sensitivity and specificity for suspicious areas on CT of 70.7% and 73.1% respectively. Evaluating disease over time, concordance between bone-maps and current practice using RECIST outcomes was 100%.This study demonstrates the feasibility and potential use of this free post-processing software in the serial assessment of osseous metastases.

Contemporary grading of prostate cancer: 2017 update for pathologists and clinicians

The Gleason grading system for prostate cancer (PCa) was developed in the 1960s by DF Gleason. Due to changes in PCa detection and treatment, the application of the Gleason grading system has changed considerably in pathology routine practice. Two consensus conferences were held in 2005 and in 2014 to update PCa Gleason grading. This review provides a summary of the changes in the grading of PCa from the original Gleason grading system to the prognostic grade grouping, as well as a discussion of the clinical significance of the percentage of Gleason patterns 4 and 5.