The impact of prognostic group classification on prostate cancer progression in intermediate-risk patients according to the European Association of Urology system: results in 479 patients treated with robot-assisted radical prostatectomy at a single tertiary referral center.

Background: Treatment outcomes in intermediate-risk prostate cancer (PCa) may be impaired by adverse pathology misclassification including tumor upgrading and upstaging. Clinical predictors of disease progression need to be improved in this category of patients. Objectives: To identify PCa prognostic factors to define prognostic groups in intermediate-risk patients treated with robot-assisted radical prostatectomy (RARP). Design: Data from 1143 patients undergoing RARP from January 2013 to October 2020 were collected: 901 subjects had available follow-up, of whom 479 were at intermediate risk. Methods: PCa progression was defined as biochemical recurrence and/or local recurrence and/or distant metastases. Study endpoints were evaluated by statistical methods including Cox's proportional hazards, Kaplan-Meyer survival curves, and binomial and multinomial logistic regression models. Results: After a median (interquartile range) of 35 months (15-57 months), 84 patients (17.5%) had disease progression, which was independently predicted by the percentage of biopsy-positive cores ⩾ 50% and the International Society of Urological Pathology (ISUP) grade group 3 for clinical factors and by ISUP > 2, positive surgical margins and pelvic lymph node invasion for pathological features. Patients were classified into clinical and pathological groups as favorable, unfavorable (one prognostic factor), and adverse (more than one prognostic factor). The risk of PCa progression increased with worsening prognosis through groups. A significant positive association was found between the two groups; consequently, as clinical prognosis worsened, the risk of detecting unfavorable and adverse pathological prognostic clusters increased in both unadjusted and adjusted models. Conclusion: The study identified factors predicting disease progression that allowed the computation of highly correlated prognostic groups. As the prognosis worsened, the risk of PCa progression increased. Intermediate-risk PCa needs more prognostic stratification for appropriate management.

A study on 479 patients looked at how prognostic group classification affects progression in patients with intermediate-risk prostate cancer treated with robot-assisted radical prostatectomy Prostate cancer is a serious health concern in men, and those with intermediate-risk prostate cancer may experience disease progression. Urologists use various methods to predict the risk of progression in these patients. However, sometimes the predictions are not accurate. Therefore, researchers conducted a study to identify factors that could help predict disease progression in patients with intermediate-risk prostate cancer who underwent robot-assisted surgery. This study on 479 patients found that a percentage of biopsy-positive cores ⩾ 50% and the International Society of Urological Pathology (ISUP) grade group 3 were predictive factors of disease progression. Additionally, factors like ISUP > 2, positive surgical margins, and pelvic lymph node invasion also predicted disease progression. Patients were classified into three groups based on their clinical and pathological features: favorable, unfavorable (one negative prognostic factor), and adverse (more than one negative prognostic factor). The risk of prostate cancer progression increased as the prognosis worsened through these groups. The study concluded that a more accurate stratification of intermediate-risk prostate cancer patients is needed to manage the disease effectively.

Advanced age is an independent prognostic factor of disease progression in high-risk prostate cancer: results in 180 patients treated with robot-assisted radical prostatectomy and extended pelvic lymph node dissection in a tertiary referral center.

OBJECTIVES: This study aimed to assess more clinical and pathological factors associated with prostate cancer (PCa) progression in high-risk PCa patients treated primarily with robot-assisted radical prostatectomy (RARP) and extended pelvic lymph node dissection (ePLND) in a tertiary referral center. MATERIALS AND METHODS: In a period ranging from January 2013 to October 2020, RARP and ePLND were performed on 180 high-risk patients at Azienda Ospedaliera Universitaria Integrata of Verona (Italy). PCa progression was defined as biochemical recurrence/persistence and/or local recurrence and/or distant metastases. Statistical methods evaluated study endpoints, including Cox's proportional hazards, Kaplan-Meyer survival curves, and binomial logistic regression models. RESULTS: The median age of included patients was 66.5 [62-71] years. Disease progression occurred in 55 patients (30.6%), who were more likely to have advanced age, palpable tumors, and unfavorable pathologic features, including high tumor grade, stage, and pelvic lymph node invasion (PLNI). On multivariate analysis, PCa progression was predicted by advanced age (≥ 70 years) (HR = 2.183; 95% CI = 1.089-4377, p = 0.028), palpable tumors (HR = 3.113; 95% CI = 1.499-6.465), p = 0.002), and PLNI (HR = 2.945; 95% CI = 1.441-6.018, p = 0.003), which were associated with clinical standard factors defining high-risk PCa. Age had a negative prognostic impact on elderly patients, who were less likely to have palpable tumors but more likely to have high-grade tumors. CONCLUSIONS: High-risk PCa progression was independently predicted by advanced age, palpable tumors, and PLNI, which is associated with standard clinical prognostic factors. Consequently, with increasing age, the prognosis is worse in elderly patients, who represent an unfavorable age group that needs extensive counseling for appropriate and personalized management decisions.

Prospective Implementation and Early Outcomes of a Risk-stratified Prostate Cancer Active Surveillance Follow-up Protocol.

Background: Active surveillance (AS) is a major management option for men with early prostate cancer. Current guidelines however advocate identical AS follow-up for all without considering different disease trajectories. We previously proposed a pragmatic three-tier STRATified CANcer Surveillance (STRATCANS) follow-up strategy based on different progression risks from clinic-pathological and imaging features. Objective: To report early outcomes from the implementation of the STRATCANS protocol in our centre. Design setting and participants: Men on AS were enrolled into a prospective stratified follow-up programme. Intervention: Three tiers of increasing follow-up intensity based on National Institute for Health and Care Excellence (NICE): Cambridge Prognostic Group (CPG) 1 or 2, prostate-specific antigen density, and magnetic resonance imaging (MRI) Likert score at entry. Outcome measurements and statistical analysis: Rates of progression to CPG ≥3, any pathological progression, AS attrition, and patient choice for treatment were assessed. Differences in progression were compared with chi-square statistics. Results and limitations: Data from 156 men (median age 67.3 yr) were analysed. Of these, 38.4% had CPG2 disease and 27.5% had grade group 2 disease at diagnosis. The median time on AS was 4 yr (interquartile range 3.2-4.9) and 1.5 yr on STRATCANS. Overall, 135/156 (86.5%) men remained on AS or converted to watchful waiting and 6/156 (3.8%) stopped AS by choice by the end of the evaluation period. Of the 156 patients, 66 (42.3%) were allocated to STRATCANS 1 (least intense follow-up), 61 (39.1%) to STRATCANS 2, and 29 (18.6%) to STRATCANS 3 (highest intensity). By increasing STRATCANS tier, progression rates to CPG ≥3 and any progression events were 0% and 4.6%, 3.4% and 8.6%, and 7.4% and 22.2%, respectively (p = 0.019). Modelling resource usage suggested potential reductions in appointments by 22% and MRI by 42% compared with current NICE guideline recommendations (first 12 months of AS). The study is limited by short follow-up, a relatively small cohort, and being single centre. Conclusions: A simple risk-tiered AS strategy is possible with early outcomes supporting stratified follow-up intensity. STRATCANS implementation could de-escalate follow-up in men at a low risk of progression while husbanding resources for those who need closer follow-up. Patient summary: We report a practical way to personalise follow-up for men on active surveillance for early prostate cancer. Our method may allow reductions in the follow-up burden for men at a low risk of disease change while maintaining vigilance for those at a higher risk.

Multicenter Database of Patients with Germ-Cell Tumors: A Latin American Cooperative Oncology Group Registry (LACOG 0515).

INTRODUCTION: Germ-cell tumors (GCTs) are the most common malignancy in young men. There is a paucity of data on GCTs in developing countries. LACOG 0515 study aimed to evaluate clinical characteristics and treatment outcomes in patients with GCTs from Brazilian cancer centers. MATERIALS AND METHODS: This is a retrospective cohort study evaluating male patients diagnosed with GCTs from 2000 to 2018 in 13 Brazilian hospitals. We described baseline characteristics, progression-free survival (PFS), and overall survival (OS). RESULTS: A total of 1232 patients were included, with a median age of 30 years. Histology was seminoma in 47.1% and non-seminoma GCT (NSGCT) in 52.9%. The primary tumor site was testis in 96.5%. At diagnosis, clinical stage I was present in 68.1% and 34.7% and clinical stages IS/II/III in 31.9% and 65.2% of patients with seminoma and NSCGT, respectively. Following orchiectomy, 55.2% of patients with clinical stage I were managed with surveillance. The 5-year disease-free survival rates among patients with stage I were 98.0% in seminoma and 92.3% in NSGCT, with 5-year OS of 99.6% and 97.6%, respectively. Among patients with advanced disease (IS, II, and III), the 5-year PFS were 88.7% in seminoma and 68.7% in NSGCT, with 5y-OS of 97.6% and 82.8%, respectively. CONCLUSION: This is the largest Brazilian cohort of GCTs. Our results show a high rate of adjuvant chemotherapy in patients with clinical stage I. Although our data demonstrate slightly inferior PFS compared with the International Germ Cell Cancer Collaborative Group and other contemporary series, the OS rates were similar.

Assessing the impact of MRI based diagnostics on pre-treatment disease classification and prognostic model performance in men diagnosed with new prostate cancer from an unscreened population.

INTRODUCTION: Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population. PATIENT AND METHODS: Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm. RESULTS: Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years' respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years' time frame). CONCLUSION: MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available.

Development and External Validation of the STRATified CANcer Surveillance (STRATCANS) Multivariable Model for Predicting Progression in Men with Newly Diagnosed Prostate Cancer Starting Active Surveillance.

For men with newly diagnosed prostate cancer, we aimed to develop and validate a model to predict the risk of progression on active surveillance (AS), which could inform more personalised AS strategies. In total, 883 men from 3 European centres were used for model development and internal validation, and 151 men from a fourth European centre were used for external validation. Men with Cambridge Prognostic Group (CPG) 1-2 disease at diagnosis were eligible. The endpoint was progression to the composite endpoint of CPG3 disease or worse (≥CPG3). Model performance at 4 years was evaluated through discrimination (C-index), calibration plots, and decision curve analysis. The final multivariable model incorporated prostate-specific antigen (PSA), Grade Group, magnetic resonance imaging (MRI) score (Prostate Imaging Reporting & Data System (PI-RADS) or Likert), and prostate volume. Calibration and discrimination were good in both internal validation (C-index 0.742, 95% CI 0.694-0.793) and external validation (C-index 0.845, 95% CI 0.712-0.958). In decision curve analysis, the model offered net benefit compared to a 'follow-all' strategy at risk thresholds of ≥0.08 and ≥0.04 in development and external validation, respectively. In conclusion, our model demonstrated good accuracy and clinical utility in predicting the progression on AS at 4 years post-diagnosis. Men with lower risk predictions could subsequently be offered less-intense surveillance. Further external validation in larger cohorts is now required.

Risk stratification for prostate cancer management: value of the Cambridge Prognostic Group classification for assessing treatment allocation.

BACKGROUND: The five-tiered Cambridge Prognostic Group (CPG) classification is a better predictor of prostate cancer-specific mortality than the traditional three-tiered classification (low, intermediate, and high risk). We investigated radical treatment rates according to CPG in men diagnosed with non-metastatic prostate cancer in England between 2014 and 2017. METHODS: Patients diagnosed with non-metastatic prostate cancer were identified from the National Prostate Cancer Audit database. Men were risk stratified according to the CPG classification. Risk ratios (RR) were estimated for undergoing radical treatment according to CPG and for receiving radiotherapy for those treated radically. Funnel plots were used to display variation in radical treatment rates across hospitals. RESULTS: A total of 61,999 men were included with 10,963 (17.7%) in CPG1 (lowest risk group), 13,588 (21.9%) in CPG2, 9452 (15.2%) in CPG3, 12,831 (20.7%) in CPG4, and 15,165 (24.5%) in CPG5 (highest risk group). The proportion of men receiving radical treatment increased from 11.3% in CPG1 to 78.8% in CGP4, and 73.3% in CPG5. Men in CPG3 were more likely to receive radical treatment than men in CPG2 (66.3% versus 48.4%; adjusted RR 1.44; 95% CI 1.36-1.53; P < 0.001). Radically treated men in CPG3 were also more likely to receive radiotherapy than men in CPG2 (59.2% versus 43.9%; adjusted RR, 1.18; 95% CI 1.10-1.26). Although radical treatment rates were similar in CPG4 and CPG5 (78.8% versus 73.3%; adjusted RR 1.01; 95% CI 0.98-1.04), more men in CPG5 had radiotherapy than men in CPG4 (79.9% versus 59.1%, adjusted RR 1.26; 95% CI 1.12-1.40). CONCLUSIONS: The CPG classification distributes men in five risk groups that are about equal in size. It reveals differences in treatment practices in men with intermediate-risk disease (CPG2 and CPG3) and in men with high-risk disease (CPG4 and CPGP5) that are not visible when using the traditional three-tiered risk classification.

Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study.

BACKGROUND: The clinical pathway to detect and diagnose prostate cancer has been revolutionised by the use of multiparametric MRI (mpMRI pre-biopsy). mpMRI however remains a resource-intensive test and is highly operator dependent with variable effectiveness with regard to its negative predictive value. Here we tested the use of the phi assay in standard clinical practice to pre-select men at the highest risk of harbouring significant cancer and hence refine the use of mpMRI and biopsies. METHODS: A prospective five-centre study recruited men being investigated through an mpMRI-based prostate cancer diagnostic pathway. Test statistics for PSA, PSA density (PSAd) and phi were assessed for detecting significant cancers using 2 definitions: ≥ Grade Group (GG2) and ≥ Cambridge Prognostic Groups (CPG) 3. Cost modelling and decision curve analysis (DCA) was simultaneously performed. RESULTS: A total of 545 men were recruited and studied with a median age, PSA and phi of 66 years, 8.0 ng/ml and 44 respectively. Overall, ≥ GG2 and ≥ CPG3 cancer detection rates were 64% (349/545), 47% (256/545) and 32% (174/545) respectively. There was no difference across centres for patient demographics or cancer detection rates. The overall area under the curve (AUC) for predicting ≥ GG2 cancers was 0.70 for PSA and 0.82 for phi. AUCs for ≥ CPG3 cancers were 0.81 and 0.87 for PSA and phi respectively. AUC values for phi did not differ between centres suggesting reliability of the test in different diagnostic settings. Pre-referral phi cut-offs between 20 and 30 had NPVs of 0.85-0.90 for ≥ GG2 cancers and 0.94-1.0 for ≥ CPG3 cancers. A strategy of mpMRI in all and biopsy only positive lesions reduced unnecessary biopsies by 35% but missed 9% of ≥ GG2 and 5% of ≥ CPG3 cancers. Using PH ≥ 30 to rule out referrals missed 8% and 5% of ≥ GG2 and ≥ CPG3 cancers (and reduced unnecessary biopsies by 40%). This was achieved however with 25% fewer mpMRI. Pathways incorporating PSAd missed fewer cancers but necessitated more unnecessary biopsies. The phi strategy had the lowest mean costs with DCA demonstrating net clinical benefit over a range of thresholds. CONCLUSION: phi as a triaging test may be an effective way to reduce mpMRI and biopsies without compromising detection of significant prostate cancers.

[Morphological criteria for progression risk in patients with prostate cancer after radiation therapy].

AIM: To study an importance of new 2016 WHO histologic grading system for prostate cancer in evaluating the risk of progressing after conformal external beam radiation therapy, brachytherapy 125I and androgen deprivation therapy. MATERIALS AND METHODS: A total of 53 patients with prostate acinar adenocarcinoma were undergone to conformal external beam radiation therapy, brachytherapy 125I and androgen deprivation therapy. Age of patients was 54-80 years (68.11+/-4.7 years). T3 and T2 prostate cancer was diagnosed in 42 (79.3%) and 11 (20,7%) patients, respectively. Baseline PSA level ranged from 5.5 ng/ml to 311 ng/ml (39.7+/-7.9 ng/ml). According to the new grading system (the WHO classification, 2016), all patients were divided into five risk groups. RESULTS: Median follow-up was 64.9 months. The biochemical progression was seen in two patients, while three patients had metastatic disease. All patients with progressing prostate cancer were from IV and V prognostic groups. The 5-year progression-free survival rates for patients of IV-V and I-III groups were 44, 4% and 100%, respectively. CONCLUSIONS: According to the results of combination treatment (conformal external beam radiotherapy, brachytherapy 125I and hormonal therapy), progression-free survival rate in patients of IV (Gleason 4+4=8) and V (Gleason 4+5=9 or 5+5=10) groups, according to new WHO grading system were significantly lower, in comparison with patients of I (Gleason 3+3=6), II (Gleason 3+4=7) and III groups (Gleason 4+3=7). Our study showed that new WHO classification allows to predict the progression of prostate cancer not only after prostatectomy, but also after conformal external beam radiation therapy, combined with brachytherapy 125I and androgen deprivation therapy.

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.

The anatomy of the TNM for colon cancer.

BACKGROUND: To visualize the anatomy as revealed by dendrograms of the tumor, lymph node, and metastasis (TNM) staging system for colon cancer and compare it with the Dukes' system. METHODS: A hierarchical clustering algorithm generated tree-structured dendrograms that stratified patients according to survival only. The dendrograms were constructed with the same prognostic variables used for the TNM. Because combinations of prognostic factors were stratified only on survival, additional factors of any number and type could be integrated into the TNM without changing the TNM categories. RESULTS: The algorithm provided a step-by-step visualization of the TNM and the Dukes' system for colon cancer. Dendrograms and associated 5-year survival rates were generated for the T category only, the N category only, the T, N combination, and combinations of the T, N, and M, and the T, N, M with histological grade. Dendrograms revealed visual differences between the structure of TNM and the Dukes' system of staging. Dendrograms also revealed how variations in prognostic factors changed survival. By cutting dendrograms along their dissimilarity axis, multiple prognostic subgroups could be created for colon cancer that may reflect outcomes that are more accurate to estimate. CONCLUSIONS: Dendrograms provide a new way to view cancer patient staging. They reveal a visual step-by-step hierarchical relationship between survival rates and combinations of prognostic variables. The dendrograms also revealed fundamental differences between the TNM and the Dukes system of staging. By stratifying on survival only, additional factors including molecular factors can be added to the TNM, because it classifies patients according to survival rates only and not according to pre-set rules of prognostic factors and stage groups. The clinical implications of stratifying only survival are discussed.

Ruxolitinib - better prognostic impact in low-intermediate 1 risk score: evaluation of the 'rete ematologica pugliese' (REP) in primary and secondary myelofibrosis.

We evaluated ruxolitinib in 65 patients with myelofibrosis according to age, sex, time of diagnosis, grade of fibrosis, prognostic score risk, Janus kinase (JAK) status, primary or secondary myelofibrosis, previous treatment, and dosage. Outcome measures were response rate, time to response, duration of response, and event-free survival and survival. Kaplan and Meier curves show a significant difference in event-free survival according to the prognostic score, in favor of patients with low int1 (p = 0.0009). The Cox stepwise model confirmed the result, the int2 high-risk score being the most powerful negative independent parameter (0.001), followed by JAK (0.008); other parameters, such as diagnosis more than 5 years earlier, grade III-IV fibrosis, and ruxolitinib dose have a negligible impact. Time to response was shorter (p = 0.001) in primary myelofibrosis. In conclusion, ruxolitinib is effective, with a better outcome in patients with a low-int1 risk score. This may suggest considering an earlier administration in the disease course.

Identification of Discrete Prognostic Groups in Ewing Sarcoma.

BACKGROUND: Although multiple prognostic variables have been proposed for Ewing sarcoma (EWS), little work has been done to further categorize these variables into prognostic groups for risk classification. PROCEDURE: We derived initial prognostic groups from 2,124 patients with EWS in the SEER database. We constructed a multivariable recursive partitioning model of overall survival using the following covariates: age; stage; race/ethnicity; sex; axial primary; pelvic primary; and bone or soft tissue primary. Based on this model, we identified risk groups and estimated 5-year overall survival for each group using Kaplan-Meier methods. We then applied these groups to 1,680 patients enrolled on COG clinical trials. RESULTS: A multivariable model identified five prognostic groups with significantly different overall survival: (i) localized, age <18 years, non-pelvic primary; (ii) localized, age <18, pelvic primary or localized, age ≥18, white, non-Hispanic; (iii) localized, age ≥18, all races/ethnicities other than white, non-Hispanic; (iv) metastatic, age <18; and (v) metastatic, age ≥18. These five groups were applied to the COG dataset and showed significantly different overall and event-free survival based upon this classification system (P < 0.0001). A sub-analysis of COG patients treated with ifosfamide and etoposide as a component of therapy evaluated these findings in patients receiving contemporary therapy. CONCLUSIONS: Recursive partitioning analysis yields discrete prognostic groups in EWS that provide valuable information for patients and clinicians in determining an individual patient's risk of death. These groups may enable future clinical trials to adjust EWS treatment according to individualized risk.

Clinical, Histological and Prognosis Correlations in Diagnosis and Treatment of Gastric Cancer.

Purpose The study authors have proposed to highlight the main epidemiologic and prognostic aspects of digestive malignancies in the Dolj county population, justifying the need for permanent and detailed estimate of this phenomenon. Methods The authors of the study have proposed to outline a descriptive epidemiological panel, characteristic for the population groups at risk of developing gastric cancers and establishing clinical factors (tumor location, disease stage, type of surgery) and histological factors (histopathological type, degree of tumor differentiation) with prognostic significance having as landmark, survival rate at 5 years or disease-free survival of 5 years. Results The study was conducted on a sample of 458 patients with gastric tumors endoscopically detected, histologically confirmed and treated between 2000-2010. The epidemiological study allowed us to outline the descriptive epidemiological panel characteristic for the group of patients at risk of developing gastric cancer. Analysis of correlation between clinical parameters and histopathological parameters reached statistical threshold in multivariate statistical analysis of the localization of tumor, disease stage and histological type (p <0.0001) and the degree of differentiation of gastric carcinomas (p <0.005). Multivariate statistical analysis has detected statistically significant differences in terms of survival rate at 5 years (p> 0.001) and free interval of disease at 5 years (p> 0.001), depending on the location of the tumor, correlated with other clinical factors (disease stage, type of surgery) and histological factors (histopathological type, tumor differentiation grade), which allowed us to outline clinical, histological and prognostic groups. Conclusions Defining the clinical, histological and prognostic groups, allows an accurate assessment of patient prognosis from the time of randomization and initiation of treatment, type of surgery in advanced loco-regional, reconverted to operability, after neoadjuvant polychemotherapy being dictated by the location of the tumor (1/3 superior vs. 1 / 3 medium vs. 1/3 lower stomach).

Prediction of survival by applying current prognostic models in diffuse large B-cell lymphoma treated with R-CHOP followed by autologous transplantation.

BACKGROUND: Among the currently available prognostic models for diffuse large B-cell lymphoma (DLBCL), we investigated to determine which is most adoptable for DLBCL patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) followed by upfront autologous stem cell transplantation (auto-SCT). METHODS: We retrospectively evaluated survival differences among risk groups based on the International Prognostic Index (IPI), the age-adjusted IPI (aaIPI), the revised IPI (R-IPI), and the National Comprehensive Cancer Network IPI (NCCN-IPI) at diagnosis in 63 CD20-positive DLBCL patients treated with R-CHOP followed by upfront auto-SCT. RESULTS: At the time of auto-SCT, 74.6% and 25.4% of patients had achieved complete remission and partial remission after R-CHOP, respectively. As a whole, the 5-year overall (OS) and progression-free survival (PFS) rates were 78.8% and 74.2%, respectively. The 5-year OS and PFS rates according to the IPI, aaIPI, R-IPI, and NCCN-IPI did not significantly differ among the risk groups for each prognostic model (P-values for OS: 0.255, 0.337, 0.881, and 0.803, respectively; P-values for PFS: 0.177, 0.904, 0.295, and 0.609, respectively). CONCLUSION: There was no ideal prognostic model among those currently available for CD20-positive DLBCL patients treated with R-CHOP followed by upfront auto-SCT.

Predicting the prognosis of lung cancer: the evolution of tumor, node and metastasis in the molecular age-challenges and opportunities.

The tumor, node and metastasis (TNM) classification of malignant tumors was proposed by Pierre Denoit in the mid-20(th) century to code the anatomic extent of tumors. Soon after, it was accepted by the Union for International Cancer Control and by the American Joint Committee on Cancer, and published in their respective staging manuals. Till 2002, the revisions of the TNM classification were based on the analyses of a database that included over 5,000 patients, and that was managed by Clifton Mountain. These patients originated from North America and almost all of them had undergone surgical treatment. To overcome these limitations, the International Association for the Study of Lung Cancer proposed the creation of an international database of lung cancer patients treated with a wider range of therapeutic modalities. The changes introduced in the 7(th) edition of the TNM classification of lung cancer, published in 2009, derived from the analysis of an international retrospective database of 81,495 patients. The revisions for the 8(th) edition, to be published in 2016, will be based on a new retrospective and prospective international database of 77,156 patients, and will mainly concern tumor size, extrathoracic metastatic disease, and stage grouping. These revisions will improve our capacity to indicate prognosis and will make the TNM classification more robust. In the future the TNM classification will be combined with non-anatomic parameters to define prognostic groups to further refine personalized prognosis.

Prediction of survival by applying current prognostic models in diffuse large B-cell lymphoma treated with R-CHOP followed by autologous transplantation

BACKGROUND: Among the currently available prognostic models for diffuse large B-cell lymphoma (DLBCL), we investigated to determine which is most adoptable for DLBCL patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) followed by upfront autologous stem cell transplantation (auto-SCT). METHODS: We retrospectively evaluated survival differences among risk groups based on the International Prognostic Index (IPI), the age-adjusted IPI (aaIPI), the revised IPI (R-IPI), and the National Comprehensive Cancer Network IPI (NCCN-IPI) at diagnosis in 63 CD20-positive DLBCL patients treated with R-CHOP followed by upfront auto-SCT. RESULTS: At the time of auto-SCT, 74.6% and 25.4% of patients had achieved complete remission and partial remission after R-CHOP, respectively. As a whole, the 5-year overall (OS) and progression-free survival (PFS) rates were 78.8% and 74.2%, respectively. The 5-year OS and PFS rates according to the IPI, aaIPI, R-IPI, and NCCN-IPI did not significantly differ among the risk groups for each prognostic model (P-values for OS: 0.255, 0.337, 0.881, and 0.803, respectively; P-values for PFS: 0.177, 0.904, 0.295, and 0.609, respectively). CONCLUSION: There was no ideal prognostic model among those currently available for CD20-positive DLBCL patients treated with R-CHOP followed by upfront auto-SCT.

Stage-dependent prognostic impact of molecular signatures in clear cell renal cell carcinoma.

PURPOSE: To enhance prognostic information of protein biomarkers for clear cell renal cell carcinomas (ccRCCs), we analyzed them within prognostic groups of ccRCC harboring different tumor characteristics of this clinically and molecularly heterogeneous tumor entity. METHODS: Tissue microarrays from 145 patients with primary ccRCC were immunohistochemically analyzed for VHL (von Hippel-Lindau tumor suppressor), Ki67 (marker of proliferation 1), p53 (tumor protein p53), p21 (cyclin-dependent kinase inhibitor 1A), survivin (baculoviral IAP repeat containing 5), and UEA-1 (Ulex europaeus agglutinin I) to assess microvessel-density. RESULTS: When analyzing all patients, nuclear staining of Ki67 (hazard ratio [HR] 1.08, 95% confidence interval [CI] 1.04-1.12) and nuclear survivin (nS; HR 1.04, 95% CI 1.01-1.08) were significantly associated with disease-specific survival (DSS). In the cohort of patients with advanced localized or metastasized ccRCC, high staining of Ki67, p53 and nS predicted shorter DSS (Ki67: HR 1.07, 95% CI 1.02-1.11; p53: HR 1.05, 95% CI 1.01-1.09; nS: HR 1.08, 95% CI 1.02-1.14). In organ-confined ccRCC, patients with high p21-staining had a longer DSS (HR 0.96, 95% CI 0.92-0.99). In a multivariate model with stepwise backward elimination, tumor size and p21-staining showed a significant association with DSS in patients with "organ-confined" ccRCCs. The p21-staining increased the concordance index of tumor size from 0.75 to 0.78. In patients with "organ-confined" ccRCC, no disease-related deaths occurred in the group with p21-expression below the threshold of 32.5% p21-positive cells (log rank test: P=0.002). CONCLUSION: The prognostic information of the studied protein biomarkers depended on anatomic tumor stages, which displayed different acquired biological tumor characteristics. Analysis of prognostic factors within different clinical ccRCC groups could help to enhance their prognostic power. The p21-staining was an independent prognostic factor and increased prognostic accuracy in a predictive model in "organ-confined" ccRCC.