• Klíčová slova
• INDUSTRIAL MEDICINE *, SPIROMETRY *,
• MeSH
• lidé MeSH
• nomogramy * MeSH
• pracovní lékařství * MeSH
• spirometrie * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

PURPOSE: To investigate pathological stage at radical prostatectomy (RP) using the "Partin tables" approach in NCCN high-risk (HR) prostate cancer (PCa) patients. MATERIALS AND METHODS: Within the SEER 2010 to 2016 database, we identified 7,718 NCCN HR PCa patients. Cross-tabulation was used to illustrate the distribution of organ confined disease (OC, pT2), extra-prostatic extension (EPE, pT3a), seminal vesicles invasion (SVI, pT3b), lymph node invasion (LNI, pT2N1), extra-prostatic and lymph node invasion (EPE + LNI, pT3aN1), and seminal vescicale and lymph node invasion (SVI + LNI, pT3bN1), according to preoperative criteria, which consisted in PSA, clinical T stage, biopsy Gleason Score (GS). Binomial 95%CI was constructed for the reported proportions. RESULTS: Median (IQR) PSA levels was 9 (6-20) ng/ml. The majority of patient harbored cT1c (51%) followed by cT2 (35%) and cT3 (14%) stage. Most patients exhibited GS 4+4 (43%). Overall, 87 vs. 15 vs. 2% of patients harbored only 1 vs. 2 vs. all 3 HR criteria. At RP, OC, EPE, SVI, and LNI rates were respectively 36%, 27%, 17%, and 19%. Highest levels of OC were recorded for cT1c, PSA <10 ng/mL and biopsy GS4+4. Conversely, EPE, SVI and LNI were the highest in patients with cT3, PSA ≥20 ng/mL and GS 5+5. After stratification according to clinical stages, OC rates decreased with increasing PSA levels and GS. Conversely, EPE, SVI and LNI rates increased with increasing PSA and GS. CONCLUSION: We provide a lookup table to illustrate the relationship between clinical and pathological characteristics in NCCN HR PCa patients.

• Klíčová slova
• High-risk prostate cancer, Lookup table, Partin tables, Prostatectomy, SEE, Staging,
• MeSH
• lidé MeSH
• nádory prostaty * patologie   chirurgie   MeSH
• prostatektomie MeSH
• prostatický specifický antigen MeSH
• semenné váčky * patologie   MeSH
• staging nádorů MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Severní Amerika MeSH
• Názvy látek
• prostatický specifický antigen 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.

• Klíčová slova
• Downgrading, High risk, National Comprehensive Cancer Network, Nomogram, Prostate cancer, Very high risk,
• 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: 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.

• Klíčová slova
• IgA nephropathy, glomerulonephritis, kidney transplantation, nomogram, recurrence,
• 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: 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.

• Klíčová slova
• Bladder cancer *, Evaluation *, Nomogram *, Prediction *, Prognosis *, Radical cystectomy *, Risk *,
• MeSH
• cystektomie * metody   MeSH
• lidé MeSH
• nádory močového měchýře * farmakoterapie   chirurgie   MeSH
• neoadjuvantní terapie metody   MeSH
• nomogramy MeSH
• retrospektivní studie MeSH
• svaly patologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH

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

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.

• Klíčová slova
• Epidemiology, SVI, Surveillance, and End Results (SEER), high-risk, prostate cancer, radical prostatectomy,
• 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
• Názvy látek
• prostatický specifický antigen MeSH

OBJECTIVE: To determine sonographically the transverse diameter of the fetal thymus and present nomogram for the transverse diameter of the fetal thymus in uncomplicated singleton pregnancies between 19 and 38 weeks of gestation. SETTING: Department of Obstetrics and Gynecology, Charles University in Prague, Faculty of Medicine Hradec Kralove, University Hospital Hradec Kralove, Czech Republic. METHODS: A prospective study was performed. The transverse diameter of the fetal thymus was measured by the one experienced examiner in 198 healthy fetuses between 19 and 38 weeks of gestation. RESULTS: The transverse diameters of the fetal thymus were obtained from 183 of the 198 subjects. The regression equation was expressed as a function of gestational age: the transverse diameter of the fetal thymus (mm) = 1.001 × gestational age (week) - 0.932 or 0.143 × day - 1.34. Both the correlation coefficients, r=0.91 for weeks and r=0.92 for days were found to be highly statistically significant (p<0.0001). CONCLUSION: This study presents normative data (mean, 5th and 95th) for the ultrasound measurements of the transverse diameter of the fetal thymus in healthy singleton pregnancies.

• MeSH
• gestační stáří * MeSH
• lidé MeSH
• nomogramy * MeSH
• plod * MeSH
• regresní analýza MeSH
• těhotenství MeSH
• thymus anatomie a histologie   diagnostické zobrazování   MeSH
• ultrasonografie prenatální * MeSH
• vývoj plodu MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• těhotenství MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• hodnotící studie MeSH
• práce podpořená grantem MeSH

Limited evidence exists about preserving neurovascular bundles during radical prostatectomy (RP) for high-risk prostate cancer (HRPCa) patients. Hence, we validated an existing algorithm predicting contralateral extraprostatic extension (cEPE) risk in unilateral high-risk cases. This algorithm aims to assist in determining the suitability of unilateral nerve-sparing RP. Among 264 patients, 48 (18%) had cEPE. The risk of cECE varied: 8%, 17.2%, and 30.8% for the low, intermediate, and high-risk groups, respectively. Despite a higher risk of cECE among individuals classified as low-risk in the development group compared to the validation group, our algorithm's superiority over always/never nerve-sparing RP was reaffirmed by decision curve analysis. Therefore, we conclude that bilateral excision may not always be justified in men with unilateral HRPCa. Instead, decisions can be based on our suggested nomogram.

• MeSH
• algoritmy * MeSH
• hodnocení rizik MeSH
• individualizovaná medicína metody   MeSH
• léčba šetřící orgány * metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• nádory prostaty * chirurgie   patologie   MeSH
• nomogramy MeSH
• prostata * chirurgie   inervace   patologie   MeSH
• prostatektomie * metody   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

Several models have previously been proposed to predict the probability of non-sentinel lymph node (NSLN) metastases after a positive sentinel lymph node (SLN) biopsy in breast cancer. The aim of this study was to assess the accuracy of two previously published nomograms (MSKCC, Stanford) and to develop an alternative model with the best predictive accuracy in a Czech population. In the basic population of 330 SLN-positive patients from the Czech Republic, the accuracy of the MSKCC and the Stanford nomograms was tested by the area under the receiver operating characteristics curve (AUC). A new model (MOU nomogram) was proposed according to the results of multivariate analysis of relevant clinicopathologic variables. The new model was validated in an independent test population from Hungary (383 patients). In the basic population, six of 27 patients with isolated tumor cells (ITC) in the SLN harbored additional NSLN metastases. The AUCs of the MSKCC and Stanford nomograms were 0.68 and 0.66, respectively; for the MOU nomogram it reached 0.76. In the test population, the AUC of the MOU nomogram was similar to that of the basic population (0.74). The presence of only ITC in SLN does not preclude further nodal involvement. Additional variables are beneficial when considering the probability of NSLN metastases. In the basic population, the previously published nomograms (MSKCC and Stanford) showed only limited accuracy. The developed MOU nomogram proved more suitable for the basic population, such as for another independent population from a mid-European country.

• MeSH
• algoritmy MeSH
• biopsie sentinelové lymfatické uzliny * MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• lymfatické metastázy diagnóza   patologie   MeSH
• nádory prsu etnologie   patologie   MeSH
• nomogramy * MeSH
• prediktivní hodnota testů MeSH
• ROC křivka MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH
• Geografické názvy
• Česká republika MeSH