BACKGROUND: Prediction of side-specific extraprostatic extension (EPE) is crucial in selecting patients for nerve-sparing radical prostatectomy (RP). Multiple nomograms, which include magnetic resonance imaging (MRI) information, are available predict side-specific EPE. It is crucial that the accuracy of these nomograms is assessed with external validation to ensure they can be used in clinical practice to support medical decision-making. METHODS: Data of prostate cancer (PCa) patients that underwent robot-assisted RP (RARP) from 2017 to 2021 at four European tertiary referral centers were collected retrospectively. Four previously developed nomograms for the prediction of side-specific EPE were identified and externally validated. Discrimination (area under the curve [AUC]), calibration and net benefit of four nomograms were assessed. To assess the strongest predictor among the MRI features included in all nomograms, we evaluated their association with side-specific EPE using multivariate regression analysis and Akaike Information Criterion (AIC). RESULTS: This study involved 773 patients with a total of 1546 prostate lobes. EPE was found in 338 (22%) lobes. The AUCs of the models predicting EPE ranged from 72.2% (95% CI 69.1-72.3%) (Wibmer) to 75.5% (95% CI 72.5-78.5%) (Nyarangi-Dix). The nomogram with the highest AUC varied across the cohorts. The Soeterik, Nyarangi-Dix, and Martini nomograms demonstrated fair to good calibration for clinically most relevant thresholds between 5 and 30%. In contrast, the Wibmer nomogram showed substantial overestimation of EPE risk for thresholds above 25%. The Nyarangi-Dix nomogram demonstrated a higher net benefit for risk thresholds between 20 and 30% when compared to the other three nomograms. Of all MRI features, the European Society of Urogenital Radiology score and tumor capsule contact length showed the highest AUCs and lowest AIC. CONCLUSION: The Nyarangi-Dix, Martini and Soeterik nomograms resulted in accurate EPE prediction and are therefore suitable to support medical decision-making.
- MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie * metody MeSH
- nádory prostaty * diagnostické zobrazování patologie chirurgie MeSH
- nomogramy * MeSH
- prognóza MeSH
- prostata diagnostické zobrazování patologie chirurgie MeSH
- prostatektomie * metody MeSH
- retrospektivní studie MeSH
- roboticky asistované výkony metody MeSH
- senioři MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- validační studie MeSH
BACKGROUND: Recurrence of immunoglobulin A nephropathy (IgAN) limits graft survival in kidney transplantation. However, predictors of a worse outcome are poorly understood. METHODS: Among 442 kidney transplant recipients (KTRs) with IgAN, 83 (18.8%) KTRs exhibited biopsy-proven IgAN recurrence between 1994 and 2020 and were enrolled in the derivation cohort. A multivariable Cox model predicting allograft loss based on clinical data at the biopsy and a web-based nomogram were developed. The nomogram was externally validated using an independent cohort (n = 67). RESULTS: Patient age <43 years {hazard ratio [HR] 2.20 [95% confidence interval (CI) 1.41-3.43], P < .001}, female gender [HR 1.72 (95% CI 1.07-2.76), P = .026] and retransplantation status [HR 1.98 (95% CI 1.13-3.36), P = .016] were identified as independent risk factors for IgAN recurrence. Patient age <43 years [HR 2.77 (95% CI 1.17-6.56), P = .02], proteinuria >1 g/24 hours [HR 3.12 (95% CI 1.40-6.91), P = .005] and C4d positivity [HR 2.93 (95% CI 1.26-6.83), P = .013] were found to be associated with graft loss in patients with IgAN recurrence. A nomogram predicting graft loss was constructed based on clinical and histological variables, with a C statistic of 0.736 for the derivation cohort and 0.807 for the external validation cohort. CONCLUSIONS: The established nomogram identified patients with recurrent IgAN at risk for premature graft loss with good predictive performance.
- MeSH
- alografty patologie MeSH
- dospělí MeSH
- IgA nefropatie * komplikace chirurgie MeSH
- ledviny patologie MeSH
- lidé MeSH
- nomogramy MeSH
- přežívání štěpu MeSH
- prognóza MeSH
- recidiva MeSH
- retrospektivní studie MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Some high-risk prostate cancer (PCa) patients may show more favorable Gleason pattern at radical prostatectomy (RP) than at biopsy. OBJECTIVE: To test whether downgrading could be predicted accurately. DESIGN, SETTING, AND PARTICIPANTS: Within the Surveillance, Epidemiology and End Results database (2010-2016), 6690 National Comprehensive Cancer Network (NCCN) high-risk PCa patients were identified. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES: We randomly split the overall cohort between development and validation cohorts (both n = 3345, 50%). Multivariable logistic regression models used biopsy Gleason, prostate-specific antigen, number of positive prostate biopsy cores, and cT stage to predict downgrading. Accuracy, calibration, and decision curve analysis (DCA) tested the model in the external validation cohort. RESULTS AND LIMITATIONS: Of 6690 patients, 50.3% were downgraded at RP, and of 2315 patients with any biopsy pattern 5, 44.1% were downgraded to RP Gleason pattern ≤4 + 4. Downgrading rates were highest in biopsy Gleason pattern 5 + 5 (84.1%) and lowest in 3 + 4 (4.0%). In the validation cohort, the logistic regression model-derived nomogram predicted downgrading with 71.0% accuracy, with marginal departures (±3.3%) from ideal predictions in calibration. In DCA, a net benefit throughout all threshold probabilities was recorded, relative to treat-all or treat-none strategies and an algorithm based on an average downgrading rate of 50.3%. All steps were repeated in the subgroup with any biopsy Gleason pattern 5, to predict RP Gleason pattern ≤4 + 4. Here, a second nomogram (n = 2315) yielded 68.0% accuracy, maximal departures from ideal prediction of ±5.7%, and virtually the same DCA pattern as the main nomogram. CONCLUSIONS: Downgrading affects half of all high-risk PCa patients. Its presence may be predicted accurately and may help with better treatment planning. PATIENT SUMMARY: Downgrading occurs in every second high-risk prostate cancer patients. The nomograms developed by us can predict these probabilities accurately.
- MeSH
- lidé MeSH
- nádory prostaty * chirurgie patologie MeSH
- nomogramy * MeSH
- prostata patologie MeSH
- prostatektomie metody MeSH
- stupeň nádoru MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Contemporary seminal vesicle invasion (SVI) rates in National Cancer Comprehensive Network (NCCN) high-risk prostate cancer (PCa) patients are not well known but essential for treatment planning. We examined SVI rates according to individual patient characteristics for purpose of treatment planning. MATERIALS AND METHODS: Within Surveillance, Epidemiology, and End Results (SEER) database (2010-2015), 4975 NCCN high-risk patients were identified. In the development cohort (SEER geographic region of residence: South, North-East, Mid-West, n = 2456), we fitted a multivariable logistic regression model predicting SVI. Its accuracy, calibration, and decision curve analyses (DCAs) were then tested versus previous models within the external validation cohort (SEER geographic region of residence: West, n = 2519). RESULTS: Out of 4975 patients, 28% had SVI. SVI rate ranged from 8% to 89% according to clinical T stage, prostate-specific antigen (PSA), biopsy Gleason Grade Group and percentage of positive biopsy cores. In the development cohort, these variables were independent predictors of SVI. In the external validation cohort, the current model achieved 77.6% accuracy vs 73.7% for Memorial Sloan Kettering Cancer Centre (MSKCC) vs 68.6% for Gallina et al. Calibration was better than for the two alternatives: departures from ideal predictions were 6.0% for the current model vs 9.8% for MSKCC vs 38.5% for Gallina et al. In DCAs, the current model outperformed both alternatives. Finally, different nomogram cutoffs allowed to discriminate between low versus high SVI risk patients. CONCLUSIONS: More than a quarter of NCCN high-risk PCa patients harbored SVI. Since SVI positivity rate varies from 8% to 89%, the currently developed model offers a valuable approach to distinguish between low and high SVI risk patients.
- MeSH
- biopsie MeSH
- invazivní růst nádoru patologie MeSH
- lidé MeSH
- nádory prostaty * patologie MeSH
- nomogramy MeSH
- prostatektomie * metody MeSH
- prostatický specifický antigen MeSH
- semenné váčky patologie MeSH
- staging nádorů MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: The role of isoforms of prostate specific antigen (PSA) and other kallikrein-related markers in early detection of biochemical recurrence (BCR) after radical prostatectomy (RP) is not well known and serum PSA is currently used in preoperative risk nomograms. OBJECTIVE: The aim of this research was to study pre- and early postoperative levels of important PSA isoforms and human kallikrein-2 to determine their ability to predict BCR and identify disease persistence (DP). METHODS: This study included 128 consecutive patients who underwent RP for clinically localized prostate cancer. PSA, fPSA, %fPSA, [-2]proPSA, PHI and hK2 were measured preoperatively, at 1 and 3 months after RP. We determined the ability of these markers to predict BCR and identify DP. RESULTS: The DP and BCR rate were 11.7%and 20.3%respectively and the median follow up was 64 months (range 3-76 months). Preoperatively, the independent predictors of BCR were PSA (p-value 0.029), [-2]proPSA (p-value 0.002) and PHI (p-value 0.0003). Post-RP, PSA was the single marker correlating with BCR, both at one (p-value 0.0047) and 3 months (p-value 0.0004). PSA, fPSA, [-2]proPSA and PHI significantly correlated to DP at 1 and 3 months post-RP (p-value < 0.05), although PSA had the most significant existing correlation (p-value < 0.0001). CONCLUSIONS: [-2]proPSA and PHI are preoperative predictors of BCR and DP that outperform the currently used serum PSA. At the early postoperative period there is no additional benefit of the other markers tested.
- MeSH
- časná detekce nádoru MeSH
- lidé středního věku MeSH
- lidé MeSH
- lokální recidiva nádoru krev diagnóza genetika MeSH
- nádorové biomarkery krev MeSH
- nádory prostaty krev diagnóza genetika chirurgie MeSH
- nomogramy MeSH
- pooperační období MeSH
- prostata patologie chirurgie MeSH
- prostatektomie MeSH
- prostatický specifický antigen krev MeSH
- protein - isoformy krev genetika MeSH
- senioři MeSH
- stupeň nádoru MeSH
- tkáňové kalikreiny krev MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Cisplatin-based neoadjuvant chemotherapy (NAC) for muscle-invasive bladder cancer (MIBC) is associated with improved overall and cancer-specific survival. The post-NAC pathological stage has previously been reported to be a major determinant of outcome. OBJECTIVE: To develop a postoperative nomogram for survival based on pathological and clinical parameters from an international consortium. DESIGN, SETTING, AND PARTICIPANTS: Between 2000 and 2015, 1866 patients with MIBC were treated at 19 institutions in the USA, Canada, and Europe. Analysis was limited to 640 patients with adequate follow-up who had received three or more cycles of NAC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A nomogram for bladder cancer-specific mortality (BCSM) was developed by multivariable Cox regression analysis. Decision curve analysis was used to assess the model's clinical utility. RESULTS AND LIMITATIONS: A total of 640 patients were identified. Downstaging to non-MIBC (ypT1, ypTa, and ypTis) occurred in 271 patients (42 %), and 113 (17 %) achieved a complete response (ypT0N0). The 5-yr BCSM was 47.2 % (95 % confidence interval [CI]: 41.2-52.6 %). On multivariable analysis, covariates with a statistically significant association with BCSM were lymph node metastasis (hazard ratio [HR] 1.90 [95% CI: 1.4-2.6]; p < 0.001), positive surgical margins (HR 2.01 [95 % CI: 1.3-2.9]; p < 0.001), and pathological stage (with ypT0/Tis/Ta/T1 as reference: ypT2 [HR 2.77 {95 % CI: 1.7-4.6}; p < 0.001] and ypT3-4 [HR 5.9 {95 % CI: 3.8-9.3}; p < 0.001]). The area under the curve of the model predicting 5-yr BCSM after cross validation with 300 bootstraps was 75.4 % (95 % CI: 68.1-82.6 %). Decision curve analyses showed a modest net benefit for the use of the BCSM nomogram in the current cohort compared with the use of American Joint Committee on Cancer staging alone. Limitations include the retrospective study design and the lack of central pathology. CONCLUSIONS: We have developed and internally validated a nomogram predicting BCSM after NAC and radical cystectomy for MIBC. The nomogram will be useful for patient counseling and in the identification of patients at high risk for BCSM suitable for enrollment in clinical trials of adjuvant therapy. PATIENT SUMMARY: In this report, we looked at the outcomes of patients with muscle-invasive bladder cancer in a large multi-institutional population. We found that we can accurately predict death after radical surgical treatment in patients treated with chemotherapy before surgery. We conclude that the pathological report provides key factors for determining survival probability.
Early detection and mitigation of disease recurrence in non-small cell lung cancer (NSCLC) patients is a nontrivial problem that is typically addressed either by rather generic follow-up screening guidelines, self-reporting, simple nomograms, or by models that predict relapse risk in individual patients using statistical analysis of retrospective data. We posit that machine learning models trained on patient data can provide an alternative approach that allows for more efficient development of many complementary models at once, superior accuracy, less dependency on the data collection protocols and increased support for explainability of the predictions. In this preliminary study, we describe an experimental suite of various machine learning models applied on a patient cohort of 2442 early stage NSCLC patients. We discuss the promising results achieved, as well as the lessons we learned while developing this baseline for further, more advanced studies in this area.
- MeSH
- lidé MeSH
- nádory plic * diagnóza MeSH
- nemalobuněčný karcinom plic * diagnóza patologie MeSH
- nomogramy MeSH
- prognóza MeSH
- retrospektivní studie MeSH
- staging nádorů MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
PURPOSE: Based on data retrieved from a comprehensive multicenter database, we externally validated a published postoperative nomogram for the prediction of disease-specific survival (DSS) in patients with papillary renal cell carcinoma (papRCC). METHODS: A multicenter database containing data of 2325 patients with surgically treated papRCC was used as validation cohort. After exclusion of patients with missing data and patients included in the development cohort, 1372 patients were included in the final analysis. DSS-probabilities according to the nomogram were calculated and compared to actual DSS-probabilities. Subsequently, calibration plots and decision curve analyses were applied. RESULTS: The median follow-up was 38 months (IQR 11.8-80.7). Median DSS was not reached. The c-index of the nomogram was 0.71 (95% CI 0.60-0.83). A sensitivity analysis including only patients operated after 1998 delivered a c-index of 0.84 (95% CI 0.77-0.92). Calibration plots showed slight underestimation of nomogram-predicted DSS in probability ranges below 90%: median nomogram-predicted 5-year DSS in the range below 90% was 55% (IQR 20-80), but the median actual 5-year DSS in the same group was 58% (95% CI 52-65). Decision-curve analysis showed a positive net-benefit for probability ranges between a DSS probability of 5% and 85%. CONCLUSIONS: The nomogram performance was satisfactory for almost all DSS probabilities; hence it can be recommended for application in clinical routine and for counseling of patients with papRCC.
- MeSH
- databáze faktografické MeSH
- karcinom z renálních buněk mortalita patologie chirurgie MeSH
- kohortové studie MeSH
- lidé středního věku MeSH
- lidé MeSH
- lymfatické metastázy MeSH
- multicentrické studie jako téma MeSH
- nádory ledvin mortalita patologie chirurgie MeSH
- nomogramy * MeSH
- pooperační období MeSH
- prognóza MeSH
- senioři MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- validační studie MeSH
Most patients with chronic lymphocytic leukemia (CLL) are diagnosed with early-stage disease and managed with active surveillance. The individual course of patients with early-stage CLL is heterogeneous, and their probability of needing treatment is hardly anticipated at diagnosis. We aimed at developing an international prognostic score to predict time to first treatment (TTFT) in patients with CLL with early, asymptomatic disease (International Prognostic Score for Early-stage CLL [IPS-E]). Individual patient data from 11 international cohorts of patients with early-stage CLL (n = 4933) were analyzed to build and validate the prognostic score. Three covariates were consistently and independently correlated with TTFT: unmutated immunoglobulin heavy variable gene (IGHV), absolute lymphocyte count higher than 15 × 109/L, and presence of palpable lymph nodes. The IPS-E was the sum of the covariates (1 point each), and separated low-risk (score 0), intermediate-risk (score 1), and high-risk (score 2-3) patients showing a distinct TTFT. The score accuracy was validated in 9 cohorts staged by the Binet system and 1 cohort staged by the Rai system. The C-index was 0.74 in the training series and 0.70 in the aggregate of validation series. By meta-analysis of the training and validation cohorts, the 5-year cumulative risk for treatment start was 8.4%, 28.4%, and 61.2% among low-risk, intermediate-risk, and high-risk patients, respectively. The IPS-E is a simple and robust prognostic model that predicts the likelihood of treatment requirement in patients with early-stage CLL. The IPS-E can be useful in clinical management and in the design of early intervention clinical trials.
- MeSH
- chronická lymfatická leukemie genetika patologie terapie MeSH
- klinické zkoušky jako téma statistika a číselné údaje MeSH
- kombinovaná terapie MeSH
- lidé MeSH
- míra přežití MeSH
- mutace * MeSH
- nádorové biomarkery genetika MeSH
- následné studie MeSH
- nomogramy * MeSH
- prognóza MeSH
- progrese nemoci MeSH
- retrospektivní studie MeSH
- senioři MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- pozorovací studie MeSH
- práce podpořená grantem MeSH
BACKGROUND: The oncogenic BRAF inhibitor vemurafenib improves outcomes for patients with advanced BRAFV600 mutation-positive melanoma compared with cytotoxic chemotherapy. Vemurafenib is now approved for use in this patient population. PATIENTS AND METHODS: In this open-label, multicentre study, patients with previously treated or untreated melanoma and the BRAFV600 mutation received vemurafenib 960 mg twice daily. The primary endpoint was safety. In a post hoc analysis, overall survival (OS) was analysed according to a prognostic scoring system developed using Eastern Cooperative Oncology Group performance status, existence of brain metastases and baseline serum lactate dehydrogenase level. The index was validated using data from patients treated with vemurafenib or dacarbazine in three clinical trials and data from patients treated with vemurafenib plus cobimetinib in two studies. The study is registered with ClinicalTrials.gov (NCT01307397). RESULTS: Between March 2011 and January 2013, 3224 patients were enrolled, and 3219 patients received ≥1 dose of vemurafenib (safety population); median follow-up time was 33.4 months. Vemurafenib's long-term benefits were confirmed, and no new safety signals identified. The prognostic index showed between-group differences in OS, with tight, non-overlapping confidence intervals. Validation in a pooled group of 666 vemurafenib-treated clinical trial patients revealed a similar pattern; the pattern was similar in 280 patients treated with vemurafenib plus cobimetinib. CONCLUSIONS: Final results from the vemurafenib safety study confirm vemurafenib's tolerability in BRAFV600 mutation-positive patients and resemble those seen in real-world clinical practice. This index may be useful in patients on combination therapy and as a basis for further work.
- MeSH
- antitumorózní látky terapeutické užití MeSH
- lidé MeSH
- lymfatické metastázy MeSH
- melanom farmakoterapie genetika patologie MeSH
- míra přežití MeSH
- mutace * MeSH
- nádory mozku farmakoterapie genetika sekundární MeSH
- následné studie MeSH
- nomogramy * MeSH
- prognóza MeSH
- protoonkogenní proteiny B-raf genetika MeSH
- senioři MeSH
- validační studie jako téma MeSH
- vemurafenib terapeutické užití MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH
