Predicting the risk of pT3a stage in cT1 clear cell renal cell carcinoma

Construction of a Model for Predicting the Risk of pT3 Based on Perioperative Characteristics in cT1 Renal Cell Carcinoma: A Retrospective Study at a Single Institution

INTRODUCTION

This study explored the predictors of upstaging and multiple sites of extension, and constructed a predictive model based on perioperative characteristics to calculate the risk of upstaging of cT1 renal cell carcinoma to pT3.

METHODS

We retrospectively reviewed 1012 patients diagnosed with cT1 renal cell carcinoma who underwent surgical treatment at the Affiliated Hospital of Qingdao University between June 2016 and August 2021. The continuous and categorical variables were analyzed using the Mann-Whitney U test and Chi-square test, respectively. After randomly dividing patients into a training set and an internal validation set with a ratio of 7:3, univariate and multivariate logistic regression analyses were used to explore the predictors of upstaging and multiple sites of extension. A nomogram model was established based on the predictors of upstaging and was validated.

RESULTS

Ninety-one cases (8.99%) of renal cell carcinoma were upstaged to pT3. In the training set, multivariate logistic regression identified the following predictors of upstaging: maximum tumor diameter, hilus involvement, tumor necrosis, tumor edge irregularity, symptoms, smoking, and platelet-lymphocyte ratio. A nomogram model was established based on the predictors. The area under the receiver operating characteristic curve was 0.810 in the training set, and 0.804 in the validation set. A 10-fold internal cross-validation conducted 200 times showed that the mean area under the curve was 0.797. The calibration curve and decision curve analysis suggested that the nomogram had robust clinical predictive power. Analyses showed higher neutrophil-lymphocyte ratio and tumor necrosis were associated with multiple sites of extrarenal extension in patients with pT3a renal cell carcinoma.

CONCLUSIONS

We identified 7 predictors of upstaging to pT3 and 2 predictors of multiple sites of extension. A nomogram model was constructed with satisfactory accuracy for predicting upstaging to pT3.

ctDNA predicts clinical T1a to pathological T3a upstaging after partial nephrectomy

Most patients diagnosed with clear cell renal cell carcinoma (ccRCC) are also detected with small and organ-confined tumors, and the majority of these are classified as clinical tumor stage 1a (cT1a). A considerable proportion of patients with cT1 RCC shows tumor upstaging to pathological stage 3a (pT3a), and these patients have worse oncological outcomes. The role of circulating tumor DNA (ctDNA) in RCC has been limited to monitoring treatment response and resistance. Therefore, the present study aimed to evaluate the potential of ctDNA in predicting pT3a upstaging in cT1a ccRCC. We sequenced plasma samples preoperatively collected from 48 patients who had undergone partial nephrectomy for cT1a ccRCC using data from a prospective cohort RCC. The ctDNA were profiled and compared with clinicopathological ccRCC features to predict pT3a upstaging. Associations between ctDNA, tumor complexity, and pT3a upstaging were evaluated. Tumor complexity was assessed using the anatomical classification system. Univariate analysis used chi-squared and Student's t-tests; multivariate analysis considered significant factors from univariate analyses. Of the 48 patients with cT1a ccRCC, 12 (25%) were upstaged to pT3a, with ctDNA detected in 10 (20.8%), predominantly in patients with renal sinus fat invasion (SFI; n = 8). Among the pT3a group, ctDNA was detected in 75%, contrasting with only 2.8% in patients with pT1a (1/36). Detection of ctDNA was the only significant preoperative predictor of pT3a upstaging, especially in SFI. This study is the first to suggest ctDNA as a preoperative predictor of pT3a RCC upstaging from cT1a based on preoperative radiological images.

Patient and tumor characteristics of histological subtypes of renal cell carcinoma and its risk of upstaging to ≥pT3

OBJECTIVE

To explore how histological subtypes impact upstaging to nonorgan confined renal cell carcinoma (≥pT3 RCC) in patients treated with partial/radical nephrectomy for cT1-2 RCC.

MATERIALS AND METHODS

We relied on an institutional tertiary-care database to identify RCC patients treated with partial/radical nephrectomy between January 2002 and December 2021. Patients were stratified according to histological subtype of RCC. Upstaging was defined as any cT1-2 tumor classified as ≥pT3 at final pathology. Uni- and multivariable logistic regression models were fitted to predict upstaging.

RESULTS

Of overall 1,020 surgically treated RCC patients, 743 harbored clear-cell (72.8%) vs. 193 (18.9%) papillary vs. 49 (4.8%) chromophobe vs. each 4 (0.4%) collecting duct and sarcomatoid vs. 27 (2.6%) other/mixed pathology of RCC. Median tumor size ranged from 3.0 cm (mixed RCC) to 7.7 cm (sarcomatoid RCC). In total, upstaging rate to ≥pT3 was 22% and ranged from 6.1% (chromophobe RCC) to 75% (collecting duct RCC). In univariable logistic regression models, chromophobe and papillary histological subtypes were significantly associated with lower upstaging of all cT1-2 RCC tumors. After controlling for patient and tumor characteristics in multivariable logistic regression models, papillary RCC independently lowers the risk of upstaging, even in sensitivity analyses for cT1 RCC only.

CONCLUSION

Important differences between histological subtypes of RCC exist regarding characteristics such as stage and tumor size at presentation, as well as upstaging to ≥pT3 at final pathology. Specifically, papillary RCC is significantly associated with lower chance of upstaging even after controlling for confounding parameters. The study is limited by missing central pathological/radiographic review and lack of survival analyses.

Neglected lymph nodal metastases in patients with renal cancer: when to extend the anatomical template of lymph node dissection during nephrectomy

BACKGROUND

The role of lymph node dissection (LND) in patients with renal cell carcinoma (RCC) is still controversial. However, detecting lymph node invasion (LNI) is key due to prognostic implications and to identify patients who might benefit from adjuvant therapies such as adjuvant pembrolizumab.

MATERIALS AND METHODS

Out of 796 patients, 261 (33%) received eLND, of whom 62 (8%) for suspicious lymph node (LN) metastases at preoperative staging (cN1). eLND was divided in 3 anatomical areas: (1) hilar, (2) side-specific (pre-/para-aortic or pre-/para-caval) and (3) inter-aorto-caval nodes. Overall maximum LN diameter was measured by a dedicated radiologist for each patient. Multivariable logistic regression models (MVA) were tested for the effect of maximum LN diameter in predicting the presence of nodal metastases outside the anatomical area of cN1.

RESULTS

LNI was confirmed in 50% of cN1, whilst only 13 out of 199 cN0 patients were pN1 at final histology (6.5%; p < 0.001). In a per-patient analysis, of 62 cN1 patients, 24% vs. 18% vs. 8% harboured pN1 disease only inside vs. in-outside vs. only outside the suspicious anatomical field of cN1 at preoperative CT/MRI scan. At MVA, increasing diameter of suspicious LNs was independently associated with risk of finding positive LNs outside the suspicious anatomical field (OR 1.05, 95%CI 1.02-1.11; p = 0.02).

CONCLUSIONS

Roughly 50% of cN1 patients undergoing eLND will harbour LN metastases, also outside the suspicious radiological area, and maximum LNs diameter at preoperative imaging correlates with such risk. Thus, an eLND might be justified in patients with large suspicious LN metastases, to better stage this patient population and to improve postoperative treatment management.

An external validation of the nocera nomogram: Predicting non-organ confined stage of ≥pT3 in cT1 clear cell renal cell carcinoma

Background

Only one previously published study by Nocera et al. addressed the risk of upstaging to ≥pT3 in cT1 clear cell renal cell carcinoma (ccRCC) by using characteristics of the R.E.N.A.L and PADUA score (age, tumor size, rim location, exophytic rate, polar involvement) developing an accurate nomogram. However, this nomogram has never been externally validated yet.

Material and methods

The study cohort consisted of 288 patients with cT1a-b ccRCC, diagnosed between 2008-2021 at the University Hospital Frankfurt, Germany. Analyses addressed clinical, tumor and radiographic characteristics. The external validation of the nomogram relied on accuracy calculations derived from the area under the curve of the receiver operator characteristic analysis.

Results

Overall, 11.8% (n=34) patients harbored ≥pT3 ccRCC. Median radiographic tumor size (3.6 vs. 5.3cm), R.E.N.A.L. (8 vs. 9 points) and PADUA score (9 vs. 11 points), as well as proportions of renal sinus involvement (82.4% vs. 51.6%), renal hilus involvement (44.1 vs. 13.0%), and medial rim location significantly differed between the pT1-2 and ≥pT3 group (all p ≤ 0.01). In subgroup analyses of small renal mass ccRCC patients (<4cm, cT1a), only 3.8% (n=6) patients had ≥pT3 pathology. Upstaged patients were significantly older and more frequently had endophytic tumor than pT1-2 counterparts (p<0.05). The external validation of the Nocera nomogram showed a good accuracy of 76.6%. Using the suggested cut-off of 21%, 26.5% of patients exhibited ≥pT3 ccRCC. Conversely, within patients below cut-off, 5.9% patients exhibited ≥pT3 ccRCC.

Conclusion

We reported the first external validation of the nomogram addressing the risk of ≥pT3 in cT1 ccRCC patients, demonstrating a good accuracy, with a low false-negative rate. Therefore, the nomogram can accurately be used for patients’ counselling and treatment decision making.

A novel nomogram can predict pathological T3a upstaged from clinical T1a in localized renal cell carcinoma

HYPOTHESIS

Nomogram can be built to predict the pathological T3a upstaging from clinical T1a in patients with localized renal cell carcinoma before surgery.

PURPOSE

Renal cell carcinoma (RCC) patients with clinical T1a (cT1a) disease who are upstaged to pathological T3a (pT3a) have reduced survivals after partial nephrectomy. We aimed to develop a nomogram-based model predicting pT3a upstaging in RCC patients with preoperative cT1a based on multiple preoperative blood indexes and oncological characteristics.

MATERIALS AND METHODS

Between 2010 and 2019, 510 patients with cT1a RCC were individually matched according to pT3a upstaging and pathological T1a (pT1a) at a 1:4 ratio using clinicopathologic features. Least absolute shrinkage and selection operator regression analysis was used to identify the most important risk factor from 40 peripheral blood indicators, and a predictive model was established. Multivariate logistic regression analysis was performed with the screened blood parameters and clinical data to identify significant variables. Harrell's concordance index (C-index) was applied to evaluate the accuracy of the model for predicting pT3a upstaging in patients with cT1a RCC.

RESULTS

Out of 40 blood indexes, the top ranked predictor was fibrinogen (FIB). Age, the ratio of the tumor maximum and minimum diameter (ROD), FIB, and tumor size were all independent risk factors for pT3a upstaging in multivariate analysis. A predictive ARFS model (Age, ROD, FIB, tumor Size) was established, and the C-index was 0.756 (95% CI, 0.681-0.831) and 0.712 (95% CI, 0.638-0.785) in the training and validation cohorts, respectively.

CONCLUSIONS

Older age, higher ROD, increased FIB level, and larger tumor size were independent risk factors for upstaging. The ARFS model has a high prediction efficiency for pT3a upstaging in patients with cT1a RCC.

Nomogram Predicting Downgrading in National Comprehensive Cancer Network High-risk Prostate Cancer Patients Treated with Radical Prostatectomy

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.

A Nomogram-Based Model to Predict Respiratory Dysfunction at 6 Months in Non-Critical COVID-19 Survivors

Objective

To assess the prevalence of respiratory sequelae of Coronavirus disease 2019 (COVID-19) survivors at 6 months after hospital discharge and develop a model to identify at-risk patients.

Patients and Methods

In this prospective cohort study, hospitalized, non-critical COVID-19 patients evaluated at 6-month follow-up between 26 August, 2020 and 16 December, 2020 were included. Primary outcome was respiratory dysfunction at 6 months, defined as at least one among tachypnea at rest, percent predicted 6-min walking distance at 6-min walking test (6MWT) ≤ 70%, pre-post 6MWT difference in Borg score ≥ 1 or a difference between pre- and post-6MWT oxygen saturation ≥ 5%. A nomogram-based multivariable logistic regression model was built to predict primary outcome. Validation relied on 2000-resample bootstrap. The model was compared to one based uniquely on degree of hypoxemia at admission.

Results

Overall, 316 patients were included, of whom 118 (37.3%) showed respiratory dysfunction at 6 months. The nomogram relied on sex, obesity, chronic obstructive pulmonary disease, degree of hypoxemia at admission, and non-invasive ventilation. It was 73.0% (95% confidence interval 67.3–78.4%) accurate in predicting primary outcome and exhibited minimal departure from ideal prediction. Compared to the model including only hypoxemia at admission, the nomogram showed higher accuracy (73.0 vs 59.1%, P < 0.001) and greater net-benefit in decision curve analyses. When the model included also respiratory data at 1 month, it yielded better accuracy (78.2 vs. 73.2%) and more favorable net-benefit than the original model.

Conclusion

The newly developed nomograms accurately identify patients at risk of persistent respiratory dysfunction and may help inform clinical priorities.

[Risk factors of renal sinus invasion in clinical T1 renal cell carcinoma patients undergoing nephrectomy]

OBJECTIVE

To summarize the clinicoradiological characteristics of clinical T1 renal cell carcinoma patients and to investigate the risk factors of renal sinus invasion in cT1 renal cell carcinoma patients undergoing nephrectomy.

METHODS

A retrospective study was conducted in cT1 renal cell carcinoma patients from January 2016 to August 2019 in Department of Urology, Peking University Third Hospital, who underwent partial or radical nephrectomy by analyzing clinicopathological and radiological data. The influencing factors of renal sinus invasion for cT1 renal cell carcinoma were determined by χ² test, Mann-Whitney U test and Logistic regression analysis.

RESULTS

A total of 507 patients were enrolled, including 354 males (69.8%) and 153 females (30.2%). The median age was 59 years and the median body mass index (BMI) was 25.5 kg/m². Eighteen patients (3.6%) had gross hematuria preoperatively. The median tumor diameter was 3.5 cm. Three hundred twenty-two patients (63.5%) were staged clinical T1a and 165 cases (36.5%) were staged clinical T1b. The median R.E.N.A.L. score was 8. Three hundred fifty-nine patients (70.8%) had regular tumor border and 148 (29.2%) irregular. All the patients underwent surgical treatment, including 186 (36.7%) partial nephrectomy and 321 (63.3%) radical nephrectomy. Postoperative pathology showed seventy-five patients (14.8%) had renal sinus invasion, including 18 in cT1a (5.6%) and 57 in cT1b (30.8%). Univariate analysis showed that age (P=0.020), R.E.N.A.L. score (R value, E value, N value, P < 0.001) and tumor border (P < 0.001) were associated risk factors for cT1 renal cell carcinoma with renal sinus invasion. On multivariate binary Logistic analysis, R.E.N.A.L. score (P≤0.020) and irregular tumor border (P=0.001) were independent risk factors.

CONCLUSION

For cT1 renal cell carcinoma patients undergoing nephrectomy, about 15% had renal sinus invasion postoperatively. High R.E.N.A.L. score and irre-gular tumor border help predicting cT1 renal cell carcinoma renal sinus invasion.

Added Value of Systemic Inflammation Markers in Predicting Clinical Stage T1 Renal Cell Carcinoma Pathologically Upstaged to T3a

Objectives

We aimed to determine preoperative risk factors associated with pathologic T3a (pT3a) upstaging of clinical T1 (cT1) renal cell carcinomas (RCCs) and develop a novel model capable of accurately identifying those patients at high risk of harboring occult pT3a characteristics.

Methods

A retrospective analysis of 1324 cT1 RCC patients who underwent partial nephrectomy (PN) or radical nephrectomy (RN) was performed. The study cohort was divided into training and testing datasets in a 70:30 ratio for further analysis. Univariable and multivariable logistic regression analyses were performed to identify predictors associated with cT1 to pT3a upstaging and subsequently, those significant risk factors were used to construct models. We used the area under the curve (AUC) to determine the model with the highest discrimination power. Decision curve analyses (DCAs) were applied to evaluate clinical net benefit associated with using the predictive models.

Results

The rates of upstaging were 6.1% (n = 81), 5.8% (n = 54) and 6.8% (n = 27) in the total population, training cohort and validation cohort, respectively. Tumor size, clinical T stage, R.E.N.A.L. (radius, exophytic/endophytic properties, nearness of tumor to collecting system or sinus, anterior/posterior) nephrometry score, lymphocyte to monocyte ratio (LMR), prognostic nutrition index (PNI) and albumin to globulin ratio (AGR) were significantly associated with pT3a upstaging. The model that consisted of R.E.N.A.L. score, LMR, AGR and PNI achieved the highest AUC of 0.70 in the validation cohort and yielded the highest net benefit. In the subpopulation with complete serum lipid profile, the inclusion of low-density lipoprotein cholesterol (LDL-C) and Castelli risk index-I (CRI-I) significantly improved the discrimination of model (AUC = 0.86).

Conclusions

Our finding highlights the importance of systemic inflammation response markers and serum lipid parameters in predicting pT3a upstaging. Our model had relatively good discrimination in predicting occult pT3a disease among patients with cT1 renal lesions, and the use of the model may be greatly beneficial to urologists in risk stratification and management decisions.