Comparison of outcomes for Hispanic and non-Hispanic patients with advanced renal cell carcinoma in the International Metastatic Renal Cell Carcinoma Database

BACKGROUND

Existing data on the impact of Hispanic ethnicity on outcomes for patients with renal cell carcinoma (RCC) is mixed. The authors investigated outcomes of Hispanic and non-Hispanic White (NHW) patients with advanced RCC receiving systemic therapy at large academic cancer centers using the International Metastatic Renal Cell Carcinoma Database (IMDC).

METHODS

Eligible patients included non-Black Hispanic and NHW patients with locally advanced or metastatic RCC initiating systemic therapy. Overall survival (OS) and time to first-line treatment failure (TTF) were calculated using the Kaplan-Meier method. The effect of ethnicity on OS and TTF were estimated by Cox regression hazard ratios (HRs).

RESULTS

A total of 1563 patients (181 Hispanic and 1382 NHW) (mostly males [73.8%] with clear cell RCC [81.5%] treated with tyrosine kinase inhibitor [TKI] monotherapy [69.9%]) were included. IMDC risk groups were similar between groups. Hispanic patients were younger at initial diagnosis (median 57 vs. 59 years, p = .015) and less likely to have greater than one metastatic site (60.8% vs. 76.8%, p < .001) or bone metastases (23.8% vs. 33.4%, p = .009). Median OS and TTF was 38.0 months (95% confidence interval [CI], 28.1-59.2) versus 35.7 months (95% CI, 31.9-39.2) and 7.8 months (95% CI, 6.2-9.0) versus 7.5 months (95% CI, 6.9-8.1), respectively, in Hispanic versus NHW patients. In multivariable Cox regression analysis, no statistically significant differences were observed in OS (adjusted hazard ratio [HR], 1.07; 95% CI, 0.86-1.31, p = .56) or TTF (adjusted HR, 1.06; 95% CI, 0.89-1.26, p = .50).

CONCLUSIONS

The authors did not observe statistically significant differences in OS or TTF between Hispanic and NHW patients with advanced RCC. Receiving treatment at tertiary cancer centers may mitigate observed disparities in cancer outcomes.

Fully Automated Versions of Clinically Validated Nephrometry Scores Demonstrate Superior Predictive Utility versus Human Scores

OBJECTIVE

To automate the generation of three validated nephrometry scoring systems on preoperative computerised tomography (CT) scans by developing artificial intelligence (AI)-based image processing methods. Subsequently, we aimed to evaluate the ability of these scores to predict meaningful pathological and perioperative outcomes.

PATIENTS AND METHODS

A total of 300 patients with preoperative CT with early arterial contrast phase were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer. A deep neural network approach was used to automatically segment kidneys and tumours, and then geometric algorithms were used to measure the components of the concordance index (C-Index), Preoperative Aspects and Dimensions Used for an Anatomical classification of renal tumours (PADUA), and tumour contact surface area (CSA) nephrometry scores. Human scores were independently calculated by medical personnel blinded to the AI scores. AI and human score agreement was assessed using linear regression and predictive abilities for meaningful outcomes were assessed using logistic regression and receiver operating characteristic curve analyses.

RESULTS

The median (interquartile range) age was 60 (51-68) years, and 40% were female. The median tumour size was 4.2 cm and 91.3% had malignant tumours. In all, 27% of the tumours were high stage, 37% high grade, and 63% of the patients underwent partial nephrectomy. There was significant agreement between human and AI scores on linear regression analyses (R ranged from 0.574 to 0.828, all P < 0.001). The AI-generated scores were equivalent or superior to human-generated scores for all examined outcomes including high-grade histology, high-stage tumour, indolent tumour, pathological tumour necrosis, and radical nephrectomy (vs partial nephrectomy) surgical approach.

CONCLUSIONS

Fully automated AI-generated C-Index, PADUA, and tumour CSA nephrometry scores are similar to human-generated scores and predict a wide variety of meaningful outcomes. Once validated, our results suggest that AI-generated nephrometry scores could be delivered automatically from a preoperative CT scan to a clinician and patient at the point of care to aid in decision making.

Practical Prediction of New Baseline Renal Function After Partial Nephrectomy

BACKGROUND

Partial nephrectomy (PN) is generally preferred for localized renal masses due to strong functional outcomes. Accurate prediction of new baseline glomerular filtration rate (NBGFR) after PN may facilitate preoperative counseling because NBGFR may affect long-term survival, particularly for patients with preoperative chronic kidney disease. Methods for predicting parenchymal volume preservation, and by extension NBGFR, have been proposed, including those based on contact surface area (CSA) or direct measurement of tissue likely to be excised/devascularized during PN. We previously reported that presuming 89% of global GFR preservation (the median value saved from previous, independent analyses) is as accurate as the more subjective/labor-intensive CSA and direct measurement approaches. More recently, several promising complex/multivariable predictive algorithms have been published, which typically include tumor, patient, and surgical factors. In this study, we compare our conceptually simple approach (NBGFRPost-PN = 0.90 × GFRPre-PN) with these sophisticated algorithms, presuming that an even 90% of the global GFR is saved with each PN.

PATIENTS AND METHODS

A total of 631 patients with bilateral kidneys who underwent PN at Cleveland Clinic (2012-2014) for localized renal masses with available preoperative/postoperative GFR were analyzed. NBGFR was defined as the final GFR 3-12 months post-PN. Predictive accuracies were assessed from correlation coefficients (r) and mean squared errors (MSE).

RESULTS

Our conceptually simple approach based on uniform 90% functional preservation had equivalent r values when compared with complex, multivariable models, and had the lowest degree of error when predicting NBGFR post-PN.

CONCLUSIONS

Our simple formula performs equally well as complex algorithms when predicting NBGFR after PN. Strong anchoring by preoperative GFR and minimal functional loss (≈ 10%) with the typical PN likely account for these observations. This formula is practical and can facilitate counseling about expected postoperative functional outcomes after PN.

AI-generated R.E.N.A.L.+ Score Surpasses Human-generated Score in Predicting Renal Oncologic Outcomes

OBJECTIVE

To determine whether we can surpass the traditional R.E.N.A.L. nephrometry score (H-score) prediction ability of pathologic outcomes by creating artificial intelligence (AI)-generated R.E.N.A.L.+ score (AI+ score) with continuous rather than ordinal components. We also assessed the AI+ score components' relative importance with respect to outcome odds.

METHODS

This is a retrospective study of 300 consecutive patients with preoperative computed tomography scans showing suspected renal cancer at a single institution from 2010 to 2018. H-score was tabulated by three trained medical personnel. Deep neural network approach automatically generated kidney segmentation masks of parenchyma and tumor. Geometric algorithms were used to automatically estimate score components as ordinal and continuous variables. Multivariate logistic regression of continuous R.E.N.A.L. components was used to generate AI+ score. Predictive utility was compared between AI+, AI, and H-scores for variables of interest, and AI+ score components' relative importance was assessed.

RESULTS

Median age was 60years (interquartile range 51-68), and 40% were female. Median tumor size was 4.2 cm (2.6-6.12), and 92% were malignant, including 27%, 37%, and 23% with high-stage, high-grade, and necrosis, respectively. AI+ score demonstrated superior predictive ability over AI and H-scores for predicting malignancy (area under the curve [AUC] 0.69 vs 0.67 vs 0.64, respectively), high stage (AUC 0.82 vs 0.65 vs 0.71, respectively), high grade (AUC 0.78 vs 0.65 vs 0.65, respectively), pathologic tumor necrosis (AUC 0.81 vs 0.72 vs 0.74, respectively), and partial nephrectomy approach (AUC 0.88 vs 0.74 vs 0.79, respectively). Of AI+ score components, the maximal tumor diameter ("R") was the most important outcomes predictor.

CONCLUSION

AI+ score was superior to AI-score and H-score in predicting oncologic outcomes. Time-efficient AI+ score can be used at the point of care, surpassing validated clinical scoring systems.

Trends in Lung Cancer Incidence and Mortality (1990-2019) in the United States: A Comprehensive Analysis of Gender and State-Level Disparities

PURPOSE

Lung cancer is the leading cause of cancer-related deaths in the United States. This study aims to analyze lung cancer incidence, mortality, and related statistics from 1990 to 2019, focusing on national- and state-level trends and exploring potential disparities between sexes.

METHODS

The Global Burden of Disease database was used to extract tracheal, bronchus, and lung cancer mortality data from 1990 to 2019 for both males and females and across all states of the United States. Age-standardized incidence rates, age-standardized mortality rates, disability-adjusted life years (DALYs), and mortality-to-incidence indices (MIIs) were studied to assess for gender-based, geographic, and temporal disparities. Joinpoint regression analysis was performed to further evaluate trends.

RESULTS

The incidence of these cancers in the United States decreased between 1990 and 2019 by 23.35%, with a more significant decline in males (37.73%) than females (1.41%). Similarly, for mortality, a decrease was observed for both sexes combined (26.83%), but much more significantly for males (40.23%) than females (6.01%). The MIIs decreased overall, but there were variations across states. DALYs decreased for both sexes combined, with males experiencing a larger reduction, but an increase was noted in some states for females.

CONCLUSION

This analysis reveals diverse trends pertaining to the incidence, mortality, and disability burden associated with lung cancer by sex and states in the United States, emphasizing the need for targeted interventions to reduce disparities. These findings contribute to our understanding of the current landscape of lung cancer and can inform future strategies for prevention, early detection, and management.

Trends in prostate cancer mortality in the United States of America, by state and race, from 1999 to 2019: estimates from the centers for disease control WONDER database

BACKGROUND

In the United States of America (USA), prostate cancer (PC) is the most common cancer in men and the second cause of cancer mortality. Black men (BM) have a higher incidence and worse mortality when compared to white men (WM). We compared trends in PC mortality in the USA by race and state from 1999 to 2019.

METHODS

We extracted PC mortality data from the Centers for Disease Control (CDC) WONDER database using the International Classification of Diseases (ICD) 10 code C61. Age-Standardized Mortality Rates (ASMR) were divided into racial groups and reported by year and state. Due to the lack of available data in many states, analyses were conducted only for WM and BM using Joinpoint regression for trend comparisons.

RESULTS

Between 1999-2019, ASMR decreased at the national level in Black (-44.6%), Asian (-44.8%), White (-31.8%), and American Indian or Alaskan native men (-19.0%). ASMR decreased in all states for both races. The greatest drop in ASMR was in Kentucky (-47.0%) for WM and Delaware (-57.8%) for BM. In 2019, ASMRs in BM (13.4/100 000) were significantly higher than WM (7.3/100 000), American Indian or Alaskan Native (3.2/100 000), and Asian men (3.2/100 000) (p < 0.001). The highest ASMRs were in Nebraska (33.5/100 000) for BM and Alaska (11/100 000) for WM.

CONCLUSIONS

During the last 20 years, the PC mortality rate dropped in all states for all races, suggesting an advancement in management strategies. Although a higher decrease in ASMR was observed in BM, ASMR remain higher among BM. ASMRs were also found to be increasing in many states post USPSTF guideline change (2012), indicating a need for more education around optimized prostate cancer screening.

Using IsoPSA With Prostate Imaging Reporting and Data System Score May Help Refine Biopsy Decision Making in Patients With Elevated PSA

OBJECTIVE

To assess how IsoPSA, a structure-based serum assay which has been prospectively validated in detecting clinically significant prostate cancer (csPCa), can help the biopsy decision process when combined with the prostate imaging reporting and data systems (PI-RADS).

MATERIALS AND METHODS

This was a single-center retrospective review of prospectively collected data on patients receiving IsoPSA testing for elevated PSA (>4.0ng/mL). Patients were included if they had received an IsoPSA test and prostate MRI within 1 year of IsoPSA testing, and subsequently underwent prostate biopsy. Multivariable logistic regression was used to identify predictors of (csPCa, ie, GG ≥ 2) on biopsy. Predictive probabilities for csPCa at biopsy were generated using IsoPSA and various PI-RADS scores.

RESULTS

Two hundred and 7 patients were included. Twenty-two percent had csPCa. Elevated IsoPSA ratio (defined as ≥6.0) (OR: 5.06, P = .015) and a PI-RADS 4-5 (OR: 6.37, P <.001) were significant predictors of csPCa. The combination of elevated IsoPSA ratio and PI-RADS 4-5 lesion had the highest area under the curve (AUC) (AUC: 0.83, P <.001). The predicted probability of csPCa when a patient had a negative or equivocal MRI (PI-RADS 1-3) and a low IsoPSA ratio (≤6) was <5%.

CONCLUSION

The combination of PI-RADS with IsoPSA ratios may help refine the biopsy decision-making process. In our cohort, a negative or equivocal MRI with a low IsoPSA may provide a low enough predicted probability to omit biopsy in such patients.

New drug approvals in prostate cancer and their effect on the treatment landscape

Prostate cancer is the most frequently diagnosed non-skin cancer and the second leading cause of cancer-related mortality in men in the United States. Over the past decade, the treatment landscape for advanced prostate cancer has rapidly shifted. For decades, androgen deprivation therapy has been the cornerstone of systemic treatment for patients with metastatic hormone-sensitive prostate cancer (mHSPC). However, more recently, we have seen the emergence of doublet and triplet combinations in the mHSPC setting. At the same time, there is an expanding list of treatments for patients with metastatic castration-resistant prostate cancer (mCRPC), including hormonal treatments, chemotherapy, immunotherapy, bone-targeted agents, radioligand therapy, and targeted therapy. The shifting of the treatment landscape for advanced prostate cancer has raised many questions regarding patient selection, therapy choice, and sequencing of different approved agents, particularly in the mCRPC setting with the earlier use of chemotherapy and androgen receptor signaling inhibitors. Since then, multiple trials have been conducted to improve the management of mHSPC and delay its progression to mCRPC. This review article discusses various clinical trials that focus on novel therapeutic targets for prostate cancer and how the initiation of newer clinical trials has affected older therapies and trials.

Point of care parenchymal volume analyses to estimate split renal function and predict functional outcomes after radical nephrectomy

Accurate prediction of new baseline GFR (NBGFR) after radical nephrectomy (RN) can inform clinical management and patient counseling whenever RN is a strong consideration. Preoperative global GFR, split renal function (SRF), and renal functional compensation (RFC) are fundamentally important for the accurate prediction of NBGFR post-RN. While SRF has traditionally been obtained from nuclear renal scans (NRS), differential parenchymal volume analysis (PVA) via software analysis may be more accurate. A simplified approach to estimate parenchymal volumes and SRF based on length/width/height measurements (LWH) has also been proposed. We compare the accuracies of these three methods for determining SRF, and, by extension, predicting NBGFR after RN. All 235 renal cancer patients managed with RN (2006-2021) with available preoperative CT/MRI and NRS, and relevant functional data were analyzed. PVA was performed on CT/MRI using semi-automated software, and LWH measurements were obtained from CT/MRI images. RFC was presumed to be 25%, and thus: Predicted NBGFR = 1.25 × Global GFR_Pre-RN × SRF_{Contralateral}. Predictive accuracies were assessed by mean squared error (MSE) and correlation coefficients (r). The r values for the LWH/NRS/software-derived PVA approaches were 0.72/0.71/0.86, respectively (p < 0.05). The PVA-based approach also had the most favorable MSE, which were 120/126/65, respectively (p < 0.05). Our data show that software-derived PVA provides more accurate and precise SRF estimations and predictions of NBGFR post-RN than NRS/LWH methods. Furthermore, the LWH approach is equivalent to NRS, precluding the need for NRS in most patients.

Use of IsoPSA with prostate MRI PIRADS score in biopsy decision making in patients with elevated PSA

388

Background: IsoPSA is prospectively validated to be superior to PSA and percent free PSA in predicting prostate cancer (PCa) as well as clinically significant prostate cancer. We sought to evaluate the use of IsoPSA in combination with prostate magnetic resonance imaging (MRI) and the prostate imaging reporting and data systems (PIRADS) on predicting either benign/indolent or csPCA at biopsy. Methods: This was a single center retrospective review of prospectively collected patient data that included all patients who underwent IsoPSA testing, preoperative prostate MRI and prostate biopsy from 2019-2021. Chi Squared analysis was used to assess for associations between a binary classification of low (<6) or elevated (>6) IsoPSA index, in combination with PIRADS scores in predicting either indolent/benign or csPCa at biopsy. Logistic regression was used to explore independent predictors of csPCa. Receiver Operating Curve (ROC) analysis was completed with areas under the curve (AUC) for IsoPSA and PIRADS scores, both alone and in combination. Predictive probabilities were assessed using combinations of IsoPSA thresholds and PIRADS scores. Results: 207 patients met inclusion criteria. Among patients with a negative MRI, low IsoPSA index was associated with a lower chance of csPCa compared to those with elevated IsoPSA (2% vs 15%, p<0.018). For those with a PIRADS 4-5 lesion, elevated IsoPSA index was associated with a higher chance of csPCa at biopsy compared to a low IsoPSA index (49% vs 19%, p=0.05). On multivariate analysis, elevated IsoPSA and PIRADS 4-5 were independent predictors of csPCa (p<0.001). Similarly, low IsoPSA index and negative MRI were independent predictors of benign/indolent disease at biopsy (p<0.001). Using predictive probabilities, the combination of PIRADS 4-5 with elevated IsoPSA was associated with the highest risk of csPCa (48%) and the highest AUC (0.83) for predicting csPCa. This AUC value was superior to either marker alone (0.76, 0.76) and total PSA alone (0.57) (p<0.001). Conclusions: The combination of elevated IsoPSA with adverse PIRADS score (4-5) is associated with a 48% predicted probability of csPCa at biopsy with an AUC of 0.83, which was more accurate than either marker alone. A low IsoPSA in combination with a negative MRI resulted in a 98% chance of benign/indolent disease at biopsy. These findings may prove useful for the practicing Urologist and may help guide discussions regarding the need for biopsy when interpreting various IsoPSA/PIRADS combinations. [Table: see text]

Predictive accuracy of computer-generated padua nephrometry scores based on continuous variables compared with categorical computer-generated scores and human-generated scores in predicting oncologic and perioperative outcomes

624

Background: The Preoperative Aspects and Dimensions Used for Anatomical Classification (PADUA) score is a validated predictor of a patient’s perioperative outcomes following partial nephrectomy. The use of a fully automated, unbiased and time sensitive PADUA scoring system is a novel concept that may help circumvent PADUA’s widespread adoptability. We sought to automate the scoring of preoperative computed tomography scans (CT) using a machine-learning-generated PADUA score (P-AI). In doing so, we aimed to compare P-AI’s ability to predict meaningful perioperative and oncologic outcomes as compared to human generated PADUA scores using both categorical (P-H) and continuous variables (P-AI+). Methods: 300 patients with pre-operative CT scans were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer at a single institution. A deep neural network approach was used to automatically segment kidneys and tumors and geometric algorithms were developed to estimate each component of PADUA based on the segmented regions (P-AI). Tumors were also manually scored by medical personnel blinded to the P-AI (P-H). The ability of P-AI and P-AI+ to predict meaningful perioperative and oncologic outcomes was compared to P-H using logistic regression and receiver operating characteristics (ROC) curve analyses and areas under the curve (AUC). Results: Median age was 60 years, 40% were female. Median tumor size was 4.2 cm, 91.3% had malignant tumors, including 27% and 37% with high-stage and high-grade, respectively. Both P-AI and P-H were able to predict the need for partial nephrectomy (p < 0.001). From an oncologic standpoint, P-AI and P-H were able to predict meaningful oncologic outcomes including the presence of malignancy, high grade and high stage disease (p < 0.004) although the ROC curves were not different from one another). Interestingly, when each PADUA component was left as a continuous rather than ordinal variables (P-AI+), this automated continuous score was able to predict surgical type (AUC 0.88), presence of malignancy (AUC 0.67), indolent tumors (AUC 0.79) and high grade (AUC 0.77)/high stage disease (AUC 0.82), better than both P-AI and P-H. Conclusions: When viewed along a continuous spectrum, AI generated PADUA scores (P-AI+) yields predictive surgical and oncologic outcomes superior to both categorical AI and human generated PADUA scores. If nephrometry can be calculated automatically, there is no longer a need to simplify the equations and the use of an AI generated PADUA scoring system, provides a reliable estimate of meaningful outcomes in a manner that is time sensitive and superior to human expert evaluation. Further prospective work and reproducibility from other centers is encouraged.

The impact of focal therapy tumor boards, including prostate magnetic resonance imaging overreads, in refining the selection candidacy for focal therapy patients: A prospective study

324

Background: Focal therapy (FT) for prostate cancer is increasingly recognized as an adequate therapeutic option in well selected men. Nevertheless, in-field and out-of-field recurrences at one year from treatment are notable. A multidisciplinary tumor board geared towards improving focal therapy (FTTB) patient selection is a novel concept which has not been explored. The impact of conducting prostate MRI-overreads during FTTB may also help refine FT candidacy and potentially reduce failure rates. We aimed to explore the value of a dedicated FTTB. Therein, we also evaluated the impact of prostate MRI overreads and its overall influence on FT candidacy. Methods: Single center, prospective study, incorporating a multidisciplinary bi-weekly FTTB (2021-2022) on patients being considered for FT. All prostate MRIs were re-reviewed by a single GU radiologist with >10 years prostate MR imaging experience. Outside pathology, when requested, was also re-reviewed. The impact of such tumor boards, and specifically MRI overreads on patient candidacy are presented. Results: Forty-five patients were presented at our FTTB over the span of one year. Patient demographics are presented. Thirty-nine patients were treatment naïve while six had prior radiation +/- ADT. MRI overread was performed on all treatment naïve patients (39/45, 87%) while pathology overreads on 11/45 (24.4%) Four patients were excluded upfront due to not meeting safety criteria for FT (Urolift device (n=1), J-pouch (n=1), suspicions of metastasis at time of consideration (n=2). Among those with MRI overreads 44.7% (17/39) were found to have findings that negatively impacted eligibility for FT like lesion crossing anteriorly to the urethra occurred in (9/17), multifocal disease (8/17), discordance of lesion on prior MRI (3/17) and lesion abutting rectal wall (1/17). Pathology re-review changed management for 3/11 patients with 2/3 being downgraded to GG1 disease and opting for active surveillance. Following multidisciplinary tumor boards, twelve patients (26.7%) were deemed candidates for FT. Conclusions: FTTB increases the selection scrutiny for FT candidates. MRI overreads are a meaningful part of FT tumor boards and can change candidacy based on new or meaningful findings. FTTB with prostate MR overreads should be considered as part of the selection process in FT decision making. [Table: see text]

The natural progression of patients with an IsoPSA value and its predictive ability of clinically significant prostate cancer on biopsy

325

Background: IsoPSA is a structure-based serum assay exploring the spectrum of possible prostate-specific antigen (PSA) isoforms. It was shown to outperform total and percent-free PSA in detecting clinically significant prostate cancer (csPCa) (grade group (GG) ≥2 on biopsy). IsoPSA reduced unnecessary biopsies and magnetic resonance imaging (MRI). We sought to compare the outcomes of eventual biopsy and imaging of surveilled patients with an initially normal or high IsoPSA, thus assessing IsoPSA’s prospective predictive ability of csPCa. Methods: We performed a single-center retrospective review of patients who underwent IsoPSA testing from 2017-present. Data was dichotomized into patients with normal (≤6) and high IsoPSA (>6). We collected the outcomes of any consequent IsoPSA and PSA test, prostate biopsy and MRI. We calculated the statistical IsoPSA’s characteristics for the prediction of csPCa on biopsy. Results: The median follow-up time of 811 patients who underwent IsoPSA testing was 18 months (IQR, 16.5-20). Among 443 patients with initial low IsoPSA, 5 (1.1%) had a csPCa on a subsequent biopsy, 19 (4.3%) subsequent high IsoPSA, 122 (27.5%) rising PSA, and 22 (5%) csPCa on MRI. Among 368 patients with initial high IsoPSA, 105 (28.5%) had a csPCa on a subsequent biopsy and 106 (28.8%) on an MRI. The sensitivity of IsoPSA to predict csPCa was 95.5%, and the NPV was 94.8%. Among 124 patients with high IsoPSA and initial negative biopsy, 110 had a subsequent negative and 14 a positive biopsy (10GG1 (8.1%), 4 ≥GG2 (3.2%)), with a respective median IsoPSA of 7.2 and 9.6 (p=0.007). An IsoPSA>10 generated an OR of csPCa of 7.2 (95%CI 2.1-25.2, p=0.0005). Conclusions: In 18-month follow-up, 1.1% of patients with normal IsoPSA developed csPCa compared to 28.5% of patients with high IsoPSA. In the cohort of patients with high IsoPSA and initially negative biopsy, 3.2% eventually developed csPCa, however, having a significantly higher IsoPSA than those who remained negative. The odds of having csPCa were 7 times higher with IsoPSA>10. [Table: see text]

Accuracy of fully automated, AI-generated models compared with validated clinical model to predict post-operative glomerular filtration rate after renal surgery

693

Background: The American Urologic Association (AUA) recommends estimation of the postoperative glomerular filtration rate (GFR) in patients with a renal mass to help decide between partial nephrectomy (PN) or radical nephrectomy (RN). If postoperative GFR<45 mL/min/1.73m2, a PN should be prioritized. Most existing methods to predict postoperative GFR are rarely implemented in the clinical setting due to complexity. Previously validated models based on clinical equations or kidney volumes from hand-segmented or semi-automated segmentations are quite accurate but have seen limited uptake in clinical practice. We hypothesize that we could develop an artificial intelligence (AI)-GFR prediction that would be calculated automatically on a preoperative computed tomography (CT) scan and predict a postoperative GFR as accurately as a validated clinical model. Methods: 300 patients undergoing PN or RN for renal tumor from the 2021Kidney and Kidney Tumor Segmentation Challenge(KiTS21) were analyzed. We excluded 7 patients having bilateral tumors. Preoperative GFR was the closest recorded value preoperatively and postoperative GFR≥90 days postoperatively. Split-renal-function (SRF) was determined in a fully automated way from preoperative imaging and our previously developed deep learning segmentation model. We programmed the algorithm to estimate postoperative GFR as 1.24×preoperative GFR×contralateral SRF for RN; and as 89% of the preoperative GFR for PN. We compared AI-predicted GFR to a validated clinical model (GFR=35+preoperative GFR(x0.65)-18(if radical nephrectomy)-age(x0.25)+3(if tumor size >7 cm)-2 (if diabetes)). We compared the AI and clinical model estimations of GFR to the measured postoperative GFR using correlation coefficients (R) and compared the ability of AI models to predict a postoperative GFR<45 using logistic regression and AUCs. Results: In 293 patients, the median age was 60 years ((IQR) 51-68), 40.6% were female, and 62.1% had PN. The median tumor size was 4.2 (2.6-6.1), and 91.8% of the tumors were malignant, of which 35.1% were high-grade, 25.6% were high-stage, and 21.8% had necrosis. The median R.E.N.A.L. nephrometry score was 8 (7-9). When comparing measured postoperative GFR, the correlation coefficients were 0.75 and 0.77 for the AI model and clinical models, respectively. For the prediction of a postoperative GFR< 45 ml/min/1.73m2, the AI and clinical models performed similarly (AUC of 0.89 and 0.9, respectively). Conclusions: Our study demonstrates the feasibility of a fully automated prediction of postoperative GFR based on CT imaging and baseline GFR with comparable predictive accuracy to existing validated clinical prediction models. These AI-generated predictions can be implemented for decision-making, with no clinical details, clinician time, or measurements needed.

Predictive accuracy of computer-generated C-index nephrometry scores compared with human-generated scores in predicting oncologic and perioperative outcomes

623

Background: The Centrality index (C-index) score is a validated nephrometry scoring system that requires precise measurements and mathematical calculations of cross sectional imaging. Like other nephrometry scores, its implementation has been slowed by required time investment and interobserver variability. We sought to automate this score on preoperative computerized tomography scans by developing an artificial intelligence-generated C-index score. We then aimed to evaluate its ability to predict meaningful oncologic and perioperative outcomes as compared to human-generated C-index nephrometry scores. Methods: 300 patients with preoperative computerized tomography with early arterial contrast phase were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer. A deep neural network approach was used to automatically segment kidneys and tumors, and then programed to generate the measurements and calculate C-index score. Human C-index scores were independently calculated by medical personnel blinded to AI-scores. AI- and Human score agreement was assessed using bivariate linear regression correlation and their predictive abilities for both oncologic and perioperative outcomes were assessed using logistic regression and compared with receiver operating characteristic (ROC) curve analyses with measurements of areas under the curve (AUC). Results: Median age was 60 years (IQE 51–68), and 40% were female. Median tumor size was 4.2 cm and 91.3% had malignant tumors. 27% were high stage, 37% high grade, and 63% underwent partial nephrectomy. There was significant agreement between Human scores and AI-scores on linear regression analysis (R2 = 0.738, p <0.0001). Both AI- and Human generated C-index scores similarly predicted meaningful oncologic outcomes, with lower levels of either C-index score associated with increased risk of malignant histology (H-score p = 0.018, AI score p =0.014) high-grade disease (both p <0.0001), and high stage disease (both p <0.0001). Lower levels of either AI or human generated C-index scores also predicted a radical nephrectomy rather than partial nephrectomy surgical approach (both p <0.0001). AUC measurements (Table) were similar but consistently superior for AI generated C-index scores. Conclusions: Fully automated AI-generated C-index scores are comparable to human-generated C-index scores and predict a wide variety of meaningful patient-centered outcomes. Once validated in additional populations, our results suggest that our AI generated C-index could be delivered automatically from a preoperative CT scan to a clinician and patient at the point of care to aid in decision making. [Table: see text]

Trends in oncological disease burden: A comparative study between higher and lower-middle-income countries

10560

Background: Cancer is a major cause of morbidity and mortality worldwide. Ten million cancer-related deaths were recorded in 2020, a rise of 66% over the preceding two decades. Malignancies of the breast, lung, prostate and colon account for over 40% of new cancer diagnoses worldwide. This study observes trends in oncological disease burden among higher (HIC’s) and lower-middle-income countries (LMIC’s) between 2000 and 2019. Methods: Mortality to incidence ratios (MIR) were calculated using the Global Burden of Disease database by extracting age standardized mortality and incidence rates per 100 000 for breast, lung, prostate and colorectal cancer for the years 2000-2019. The European Union (EU) 15+ countries were taken to represent HIC’s. 8 of the LMIC’s in the World Bank group were included as their data quality rating was 3/5 or higher. This cohort comprised Egypt, Sri Lanka, Ukraine, El Salvador, Republic of Moldova, Philippines, Kyrgyzstan and Nicaragua. Breast, lung, colorectal and prostate cancer were included as the tumor types with highest global incidence. Median MIR (with interquartile range) were computed for each LMIC and EU15+ groups for males and females for each of the four tumor types. Results: Between 2000 and 2019 median MIR for the LMIC group was higher than for EU15+ group for all four cancer types in males and females. Wilcoxon rank sum of the 2019 data showed a statistically significant difference (p <0.001) in MIR between HIC’s and LMIC’s (table 1). For breast, prostate and colorectal cancer the difference in median MIR between LMIC group and EU15+ decreased over the observation period, for lung cancer the difference increased. Conclusions: Globally there are wide geographical variations in MIR. Cancer outcomes appear consistently worse in LMIC’s compared to HIC’s. Availability of cancer screening, access to treatment and risk-factor prevalence may contribute to the above trends. Identifying these regional disparities provides an opportunity to target resource allocation to regions that would derive the greatest benefit. [Table: see text]

Trends of kidney cancer burden from 1990 to 2019 in European Union 15+ countries

393

Background: Kidney cancer is among the most common cancers worldwide and is increasing in incidence. During 2020, around 400,000 new cases of kidney cancer were reported, with 180,000 estimated deaths. In recent decades, significant variability in the incidence and mortality of kidney cancer has been universally reported. This study aimed to compare geographical trends in incidence, mortality, and disability-adjusted life years from kidney cancer between European Union (EU) 15+ countries from 1990 to 2019. Methods: The mortality data of kidney cancer were extracted from the Global Burden of Disease Study database. Versions 10 and 9 of the International Classification of Diseases were adopted. Age-standardized incidence rates (ASIR), age-standardized death rates (ASDR), and disability-adjusted life years (DALYs) were collected, per year and per country of the EU15+ group. Mortality-to-incidence ratios (MIR) were calculated. Data was then dichotomized into males and females. Joinpoint regression was done for analysis of trends. Results: From 1990 to 2019, ASIRs increased in most of the countries except for Luxembourg for males, the United States of America (USA) for females, and Austria and Sweden for both sexes. The largest rises of ASIRs were in Denmark for males and females (+89.3% and +82.8%, respectively). ASDRs increased in 10/19 countries for males and 9/19 in females, with the highest rise in Denmark for males and females (+41.7% and +37.7% respectively), and the largest drop in Austria for males and females (-33.8% and -35.8% respectively). MIRs decreased in all countries, for both sexes, with the widest declines in Portugal for males (-29.0%) and in Ireland for females (-26.6%). Trends in DALYs were variable, with the highest rise in Denmark for males and females (+38.6% and +30.2% respectively) and the largest drop in Austria for males and females (-39.5% and -41.2%, respectively). In 2019, the highest ASIR was observed in the USA for males (16.7/100,000) and in Finland for females (8.3/100,000), the highest ASDR in the Netherlands for males (6.1/100,000) and Finland for females (3.0/100,000), highest MIR in Sweden for both genders (0.6/100,000 each), and highest DALYs in the Netherlands for males (132.3/100,000) and in Finland for females (62.6/100,000). Conclusions: The incidence and mortality from kidney cancer rose in most EU15+ countries from 1990 to 2019. Interestingly, an improvement in the outcomes is predicted by the drop in MIR in all countries.[Table: see text]

Trends in prostate cancer mortality in the United States of America, by state and race, from 1999 to 2019: Estimates from the Centers for Disease Control WONDER database

30

Background: In the United States of America (USA), prostate cancer is the most common cancer in men, and it remained the second leading cause of cancer related mortality. It has a disproportionate burden of disease among minorities. In particular, African American (AA) men have a higher incidence and more aggressive disease course. Our study compares trends in prostate cancer mortality in the United States of America (USA) by race and state from 1999 to 2019. Methods: We used the Center for Disease Control (CDC) WONDER database using ICD-10 code C61 to extract mortality data for malignant prostate cancer. Age standardized death rates (ASDRs) are reported per 100,000 population using the USA standard population. ASDRs were divided into American Indian or Alaskan Native, Asian, Black or African American and, Whites and reported by year for each state. Due to the lack of available data in many states, state-wise analyses were done for white and African American men only. We used Joinpoint regression analysis for trends comparison. Results: Between 1999 and 2019, data was analyzed from 50 states of the USA, of which four started collecting data from 2000, one from 2001, one from 2008, and one from 2009. Three states had data until 2018 only. Data was missing for African American men in 17 states. In 2019, ASDR in African American (13.4/100,000) was significantly higher than Whites (7.3/100,000) (p<0.001). The highest ASDR for African American was observed in Nebraska (33.5/100,000), followed by Wisconsin (17.7/100,000). In contrast, the highest ASDR for whites was observed in Alaska (11/100,000), followed by Utah (10.5/100,000) ASDR decreased by 31.8% in White men at the national level, compared to a decline of 44.6% in African American men. ASDR decreased in all states for both races. For White men, the widest drops were in South Dakota (-45.9%) and Kentucky (-47.0%), and the lowest declines in New Hampshire (-11.5%) and Alaska (-16.0%). For African American men, the largest decreases were in Delaware (-57.8%) and Nevada (-55.3%), and the smallest declines were in Kentucky (-14.9%) and Wisconsin (-20.3%). Conclusions: During the last 20 years, the mortality rate from prostate cancer has consistently dropped in all the states of the USA and for all races. Even though a higher decrease in ASDR was observed in the African American and Asian racial groups, ASDR is still higher in African Americans as compared to Whites.[Table: see text]

Trends in disease burden from prostate cancer amongst different regions of the world and extensively the European Union 15+ countries, from 1990 to 2019: Estimates from the Global Burden of Disease study

187

Background: Prostate cancer was the third most commonly diagnosed cancer in 2020 and the fifth leading cause of cancer mortality worldwide. Global variations in the burden of prostate cancer have been observed in the past decades. This study aimed to assess the trends in incidence, mortality, and disability-adjusted life years from prostate cancer in the World Health Organization (WHO) regions and extensively in the European Union (EU) 15+ countries from 1990 to 2019. Methods: The Global Burden of Disease Study database was used to extract the mortality data of prostate cancer, based on the International Classification of Diseases versions 10 and 9. Data acquired for different WHO regions and each country of the EU15+ nations, per year from 1990 to 2019, included age-standardized incidence rates (ASIR), age-standardized death rates (ASDR), and disability-adjusted life years (DALYs). Mortality-to-incidence ratios (MIR) were then computed. Trends were assessed using Joinpoint regression. Results: Between 1990 and 2019, ASIRs increased worldwide (+13.16%), except in the American region, with the largest growth in the Eastern Mediterranean Region (EMR) (+72.43%). While ASDRs and DALYs increased in Africa, South-East Asia, and EMR, they decreased in the Americas, Europe, and Western Pacific Region (WPR). MIRs decreased universally (-25.52%), mainly in the WPR (-43.49%). In EU15+ countries, ASIRs increased in all countries, except for Canada (-11.27%) and the United States of America (USA) (-10.37%), with the largest rise in Finland (+75.11%). ASDRs decreased in all countries, with the widest drop in Luxembourg (-41.89%) and the lowest in Denmark (-13.96%). MIRs decreased in all countries, with the highest drop in Finland (-55.37%). Similarly, DALYs decreased in all countries, with the highest decrease in Luxembourg (-40.56%). In 2019, the highest ASIR was in the USA (118.24/100,000), whereas Denmark had the highest ASDR (31.35/100,000), MIR (0.38/100,000), and DALY (498.03/100,000). Conclusions: Over the 30 years, the incidence of prostate cancer has been rising worldwide, excluding Canada and the USA. However, the universal decrease of MIRs highlights improved outcomes and efficient screening and therapeutic strategies. All indices are represented per 100,000 population.[Table: see text]

P3603Impact of idiopathic thrombocytopenic purpura on clinical outcomes in patients with acute myocardial infarction

Background

There is scarce evidence reflecting the clinical outcomes in patients with Idiopathic Thrombocytopenic Purpura (ITP) and Acute Myocardial Infarction (AMI). The ITP patient population is at higher risk of bleeding complications due to low platelet counts and difficulty in managing their antiplatelet and anticoagulation therapy. In our study, we sought to assess clinical outcomes of ITP patients admitted with AMI using the US national inpatient sample (NIS) database.

Purpose

To determine difference in in-hospital mortality, clinical complications, and length of stay (LOS) in AMI patients with and without ITP.

Methods

We identified adults aged ≥18 years hospitalized from 2005 to 2014 with AMI as their primary diagnosis utilizing ICD-9 codes 410.0 to 410.92. Patients with ITP were identified using ICD-9 code 287.31. The primary outcome was in-hospital mortality. Secondary outcomes included coronary revascularization procedures (PCI and CABG), and in-hospital complications including bleeding (intracranial, epistaxis, GI, and GU bleeding, hematoma, and bleeding requiring transfusion), cardiac complications, transfusions, acute ischemic stroke (AIS), and LOS. A propensity-matched cohort accounting for demographic characteristics, comorbidities, and cardiovascular risk factors, was created to compare these outcomes. Patients with secondary causes of ITP such as HIV, pregnancy, sepsis, SLE, malignancy were excluded.

Results

A total of 1108034 AMI admissions, of which 1002 with ITP, were identified. In the unmatched group, patients with ITP were older, and had more comorbidities (diabetes mellitus; hypothyroidism; atrial fibrillation; previous history of cardiovascular, peripheral, and end stage renal disease; all p<0.05). In the AMI population, 851 ITP and 851 non-ITP admissions were propensity-matched. Figure 1 illustrates the primary and secondary outcomes of the study among the propensity-matched study groups. Although there was no difference in short-term mortality between the ITP and non-ITP patients with AMI, patients with ITP were less likely to undergo coronary revascularization possibly because of thrombocytopenia. Patients with ITP had significantly more bleeding complications and transfusions. We observed in our study that patients with ITP had a significantly longer LOS compared to non-ITP patients (6.1 vs 5.4 days, with a mean ratio of 1.14 (95% CI: 1.05,1.23)).

Conclusion

In the large population of patients included in the NIS database, patients with ITP admitted with AMI, have a significantly higher rate of bleeding complications, undergo less PCI and have a longer LOS compared to AMI patients without ITP. There are no current guidelines by ACC/AHA/ESC regarding management of patients with AMI and thrombocytopenia. These results warrant further investigation through randomized controlled trials including patients with thrombocytopenia to assess long term outcomes and to define optimal management in this population.

Assessing the performance of a method of simultaneous compression and encryption of multiple images and its resistance against various attacks

We introduce a double optimization procedure for spectrally multiplexing multiple images. This technique is adapted from a recently proposed optical setup implementing the discrete cosine transformation (DCT). The new analysis technique is a combination of spectral fusion based on the properties of DCT, specific spectral filtering, and quantization of the remaining encoded frequencies using an optimal number of bits. Spectrally multiplexing multiple images defines a first level of encryption. A second level of encryption based on a real key image is used to reinforce encryption. A set of numerical simulations and a comparison with the well known JPEG (Joint Photographic Experts Group) image compression standard have been carried out to demonstrate the improved performances of this method. The focus here will differ from the method of simultaneous fusion, compression, and encryption of multiple images (SFCE) [Opt. Express 19, 24023 (2011)] in the following ways. Firstly, we shall be concerned with optimizing the compression rate by adapting the size of the spectral block to each target image and decreasing the number of bits required to encode each block. This size adaptation is achieved by means of the root-mean-square (RMS) time-frequency criterion. We found that this size adaptation provides a good tradeoff between bandwidth of spectral plane and number of reconstructed output images. Secondly, the encryption rate is improved by using a real biometric key and randomly changing the rotation angle of each block before spectral fusion. By using a real-valued key image we have been able to increase the compression rate of 50% over the original SFCE method. We provide numerical examples of the effects for size, rotation, and shifting of DCT-blocks which play noteworthy roles in the optimization of the bandwidth of the spectral plane. Inspection of the results for different types of attack demonstrates the robustness of our procedure.

Simultaneous fusion, compression, and encryption of multiple images

We report a new spectral multiple image fusion analysis based on the discrete cosine transform (DCT) and a specific spectral filtering method. In order to decrease the size of the multiplexed file, we suggest a procedure of compression which is based on an adapted spectral quantization. Each frequency is encoded with an optimized number of bits according its importance and its position in the DC domain. This fusion and compression scheme constitutes a first level of encryption. A supplementary level of encryption is realized by making use of biometric information. We consider several implementations of this analysis by experimenting with sequences of gray scale images. To quantify the performance of our method we calculate the MSE (mean squared error) and the PSNR (peak signal to noise ratio). Our results consistently improve performances compared to the well-known JPEG image compression standard and provide a viable solution for simultaneous compression and encryption of multiple images.

Predicting and monitoring tumor response to epidermal growth factor receptor inhibitor gefitinib in patients with locally advanced esophageal adenocarcinoma

14112

Background: This study aimed to validate an ex vivo chemosensitivity assay to measure the pharmacodynamic effect of gefitinib on esophageal adenocarcinoma (EAC) prior to treatment with pre-operative concomitant chemoradiotherapy (CRT). Methods: A 14 day run-in period with 250 mg/day of gefitinib preceded CRT. Endoscopic biopsies (D 0 and 14) in 4 patients with T2–3N0/1M0/1a EAC were analyzed by ex vivo chemosensitivity assay. Day 0 tissue was exposed to gefitinib ex vivo, then tumor was exposed to gefitinib for 14 days in vivo (ie in the patient). Phosphorylation of the EGFR, raf/MEK/ERK and PI3/AKT pathways was measured by Western blot. Profiles were compared for correlation between ex vivo and in vivo exposure, and patterns were correlated with response to CRT. The effects were also characterized by immunohistochemistry (IHC). EGFR, K-Ras, and PI3K mutations, serum concentrations of gefitinib and PTEN status were measured as potential confounders. Results: One patient with stage T3N1 died of unexplained hemorrhage during surgery. Three had clinical and path stages of: T3N1/T0N0, T3N0/T3N0, T3N1/T2N1. Gefitinib levels were constant, confirming exposure of target tissue to the drug. Ex vivo exposure yielded four distinct pathway patterns. The exact same patterns were seen after in vivo exposure. No mutations were identified in exons 18–21 of the EGFR, exons 2/3 of K-ras or exons 9/22 of PI3K. PTEN levels were similar in all tumors. PCNA expression correlated with raf/MEK/ERK pathway inhibition, but not with inhibition of EGFR activity. IHC correlated with Western blot for expression of EGFR, and phospho- and total ERK levels. No correlation was observed between gefitinib effect and pathologic response to CRT. Conclusions: This study used a novel ex vivo chemosensitivity assay to demonstrate the activity of gefitinib to inhibit target in tumor tissue obtained from patients with EAC. The exact correlation of pre- and post-treatment profiles suggests potential use in the pre-treatment setting to predict in vivo effects of targeted therapies. This approach may facilitate the further refinement of patient selection to maximize potential benefit while sparing patients unlikely to respond to a given agent.

No significant financial relationships to disclose.

The effect of fertilizer treatments on yield of seed and volatile oil of fennel (Foeniculum vulgare Mill.)

Nitrogen fertilization gave higher number of compound umbels and increased oil percentage, seed yield and oil yield with increase in dose. Phosphorus and potassium produced significant increase in the previons aspects with the second dose only.

The effect of date of sowing and plant spacing on yield of seed and volatile oil of fennel (Foeniculum vulgare Mill.)

Wider spacing produced taller fennel plants. The compound umbels per plant increased as the distance between plants increased. The yield of seed per plant was greater in wider spacing. On the other hand, the medium space (30 cm) produced higher seed and oil contant per acre. Early sown plants produced taller plants, with higher compound umbels. The oil percentage was not affected while higher yield of seed and oil were significantly obtained.