NCCN Guidelines® Insights: Bladder Cancer, Version 3.2024.

Bladder cancer, the sixth most common cancer in the United States, is most commonly of the urothelial carcinoma histologic subtype. The clinical spectrum of bladder cancer is divided into 3 categories that differ in prognosis, management, and therapeutic aims: (1) non-muscle-invasive bladder cancer (NMIBC); (2) muscle invasive, nonmetastatic disease; and (3) metastatic bladder cancer. These NCCN Guidelines Insights detail recent updates to the NCCN Guidelines for Bladder Cancer, including changes in the fifth edition of the WHO Classification of Tumours: Urinary and Male Genital Tumours and how the NCCN Guidelines aligned with these updates; new and emerging treatment options for bacillus Calmette-Guérin (BCG)-unresponsive NMIBC; and updates to systemic therapy recommendations for advanced or metastatic disease.

NCCN Guidelines® Insights: Prostate Cancer, Version 3.2024.

The NCCN Guidelines for Prostate Cancer include recommendations for staging and risk assessment after a prostate cancer diagnosis and for the care of patients with localized, regional, recurrent, and metastatic disease. These NCCN Guidelines Insights summarize the panel's discussions for the 2024 update to the guidelines with regard to initial risk stratification, initial management of very-low-risk disease, and the treatment of nonmetastatic recurrence.

Risk factors and health behaviors associated with loneliness among cancer survivors during the COVID-19 pandemic.

Loneliness may exacerbate poor health outcomes particularly among cancer survivors during the COVID-19 pandemic. Little is known about the risk factors of loneliness among cancer survivors. We evaluated the risk factors of loneliness in the context of COVID-19 pandemic-related prevention behaviors and lifestyle/psychosocial factors among cancer survivors. Cancer survivors (n = 1471) seen at Huntsman Cancer Institute completed a survey between August-September 2020 evaluating health behaviors, medical care, and psychosocial factors including loneliness during COVID-19 pandemic. Participants were classified into two groups: 'lonely' (sometimes, usually, or always felt lonely in past month) and 'non-lonely' (never or rarely felt lonely in past month). 33% of cancer survivors reported feeling lonely in the past month. Multivariable logistic regression showed female sex, not living with a spouse/partner, poor health status, COVID-19 pandemic-associated lifestyle factors including increased alcohol consumption and marijuana/CBD oil use, and psychosocial stressors such as disruptions in daily life, less social interaction, and higher perceived stress and financial stress were associated with feeling lonely as compared to being non-lonely (all p < 0.05). A significant proportion of participants reported loneliness, which is a serious health risk among vulnerable populations, particularly cancer survivors. Modifiable risk factors such as unhealthy lifestyle behaviors and psychosocial stress were associated with loneliness. These results highlight the need to screen for unhealthy lifestyle factors and psychosocial stressors to identify cancer survivors at increased risk of loneliness and to develop effective management strategies.

The Ability of the STAR-CAP Staging System to Prognosticate the Risk of Subsequent Therapies and Metastases After Initial Treatment of M0 Prostate Cancer.

INTRODUCTION: The International Staging Collaboration for Prostate Cancer (STAR-CAP) has been proposed as a risk model for prostate cancer with superior prognostic power compared to the current staging system. This study aimed to evaluate the performance of STAR-CAP in predicting the risk of subsequent therapy after initial treatment and the risk of developing metastases. PATIENTS AND METHODS: The study included 3425 men from an institutional observational registry with a median age of 64.9 years and a median follow-up time of 5.4 years. The primary endpoints were metastases and progression to additional therapy after initial therapy (radiation ± surgery). The risk of progression in the STAR-CAP group was estimated using a competing risk model (death). RESULTS: The results showed that patients with STAR-CAP stages 1A-1C had a similar risk of requiring additional therapies and developing metastasis. Compared to stage IC, each stage from 2A to 3B incrementally increased the risk of subsequent therapy (hazard ratio (HR) 1.4-5.8, respectively) and metastases (HR 1.5-10.8, respectively). The 5-year probability of receiving subsequent therapy for a patient with stage IC was 8.6%, which increased from 11.4% to 37.4% for those with stages 2A to 3B. The 5-year probability of developing metastases for patients with stage IC was 1.5%, which increased from 2.2% to 8.2% for patients with stages 2A to 3B. CONCLUSIONS: The probability of receiving subsequent therapy was higher for patients undergoing surgery, while radiation therapy patients were more likely to receive treatment with intensified multimodality therapies upfront.

Validation of the Combined Clinical Cell-Cycle Risk Score to Prognosticate Early Prostate Cancer Metastasis From Biopsy Specimens and Comparison With Other Routinely Used Risk Classifiers.

PURPOSE: We aim to independently validate the prognostic utility of the combined cell-cycle risk (CCR) multimodality threshold to estimate risk of early metastasis after definitive treatment of prostate cancer and compare this prognostic ability with other validated biomarkers. METHODS: Patients diagnosed with localized prostate cancer were enrolled into a single-institutional registry for the prospective observational cohort study. The primary end point was risk of metastasis within 3 years of diagnostic biopsy. Secondary end points included time to definitive treatment, time to subsequent therapy, and metastasis after completion of initial definitive treatment. Multivariable cause-specific Cox proportional hazards regression models were produced accounting for competing risk of death and stratified on the basis of the CCR active surveillance and multimodality (MM) thresholds. Time-dependent areas under the receiver operating characteristic curve were calculated. RESULTS: The cohort consisted of 554 men with prostate cancer and available CCR score from biopsy. The CCR score was prognostic for metastasis (hazard ratio [HR], 2.32 [95% CI, 1.17 to 4.59]; P = .02), with scores above the MM threshold having a higher risk than those below the threshold (HR, 5.44 [95% CI, 2.72 to 10.91]; P < .001). The AUC for 3-year risk of metastasis on the basis of CCR was 0.736. When men with CCR above the MM threshold received MM therapy, their 3-year risk of metastasis was significantly lower than those receiving single-modality therapy (3% v 14%). Similarly, a CCR score above the active surveillance threshold portended a faster time to first definitive treatment. CONCLUSION: CCR outperforms other commonly used biomarkers for prediction of early metastasis. We illustrate the clinical utility of the CCR active surveillance and multimodality thresholds. Molecular genomic tests can inform patient selection and personalization of treatment for localized prostate cancer.

The impact of a positive COVID-19 test on timeliness of radiation in patients receiving brachytherapy.

BACKGROUND: Delays in initiating and completing brachytherapy may have adverse oncologic outcomes for patients with cervical, uterine, and prostate cancer. The impact of the COVID-19 pandemic on brachytherapy in the United States has not been well-characterized. OBJECTIVES: We aim to evaluate how a positive COVID-19 test affected timeliness of treatment for patients undergoing brachytherapy for cervical, uterine, and prostate cancer. METHODS: We queried the National Cancer Database to identify patients diagnosed with cervical, uterine, and prostate cancer in 2019 and 2020 who received brachytherapy in their treatment. Patients who tested positive for COVID-19 between cancer diagnosis and start of radiation were compared to those who did not test positive for COVID-19. Time in days from cancer diagnosis to initiation of radiation was compared using two-sample t-tests with p < 0.05 signifying significant differences. RESULTS: We identified 38,341 patients with cervical (n = 6,925), uterine (n = 18,587), and prostate cancer (n = 12,829). Rates of COVID-19 positivity were cervical cancer (n = 135; 2%), uterine cancer (n = 236; 1.3%), and prostate cancer (n = 141; 1%). Of those, 35% of cervical, 49% of uterine, and 43% of prostate cancer patients tested positive between their cancer diagnosis and initiation of radiation. Median days to radiation was significantly longer in these patients: 78 versus 51 for cervical cancer (p < 0.01), 150 versus 104 for uterine cancer (p < 0.01), and 154 versus 124 for prostate cancer (p < 0.01). CONCLUSIONS: For patients with cervical, uterine, and prostate cancer diagnosed between 2019-2020, testing positive for COVID-19 after their cancer diagnosis was associated with a delay to initiation of radiation by 4-7 weeks.

Using the Cell-Cycle Risk Score to Predict the Benefit of Androgen-Deprivation Therapy Added to Radiation Therapy in Patients With Newly Diagnosed Prostate Cancer.

PURPOSE: Guidelines recommend adding androgen-deprivation therapy (ADT) to radiation therapy (RT) in certain patients with localized prostate cancer. Individualized genomic testing may improve the prognostic accuracy of risk assessments. Herein, we describe a mathematical model of the benefit of adding ADT to RT as a function of the personalized clinical cell-cycle risk (CCR) score to inform 10-year metastasis risk. METHODS: A model of absolute risk reduction (ARR) was built using a retrospective cohort of men tested with Prolaris who received RT alone (N = 467). The relative benefit of ADT added to RT to reduce distant metastasis was estimated at 41% on the basis of a meta-analysis of randomized trials. The ARR and number needed to treat (NNT) were computationally derived in patients clinically tested with Prolaris between January 1, 2020, and October 31, 2022 (N = 56,485). Risks were predicted using a cause-specific Cox proportional hazards model with CCR score predicting time to metastasis. A CCR score of 2.112 represents the validated multimodal treatment (MMT) threshold. RESULTS: The ARR from ADT increased from almost zero at low CCR scores to 17.1% at CCR = 3.690 with the corresponding NNT = 6, indicating that adding ADT to RT would prevent metastasis within 10 years for one of every six treated individuals. In the clinical cohort, the average ARR was 0.86% in individuals under the MMT threshold (NNT = 116). The average ARR was 8.19% in individuals above the MMT threshold (NNT = 12). Broad ranges of ADT benefit were observed within National Comprehensive Cancer Network risk categories. CONCLUSION: The precise and personalized risk estimate of metastasis provided by the CCR score can help inform patients and physicians when considering treatment intensification.

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life, and there remain no validated predictive models to guide its use. METHODS: We used digital pathology images from pretreatment prostate tissue and clinical data from 5727 patients enrolled in five phase 3 randomized trials, in which treatment was radiotherapy with or without ADT, as our data source to develop and validate an artificial intelligence (AI)­derived predictive patient-specific model that would determine which patients would develop the primary end point of distant metastasis. The model used baseline data to provide a binary output that a given patient will likely benefit from ADT or not. After the model was locked, validation was performed using data from NRG Oncology/Radiation Therapy Oncology Group (RTOG) 9408 (n=1594), a trial that randomly assigned men to radiotherapy plus or minus 4 months of ADT. Fine­Gray regression and restricted mean survival times were used to assess the interaction between treatment and the predictive model and within predictive model­positive, i.e., benefited from ADT, and ­negative subgroup treatment effects. RESULTS: Overall, in the NRG/RTOG 9408 validation cohort (14.9 years of median follow-up), ADT significantly improved time to distant metastasis. Of these enrolled patients, 543 (34%) were model positive, and ADT significantly reduced the risk of distant metastasis compared with radiotherapy alone. Of 1051 patients who were model negative, ADT did not provide benefit. CONCLUSIONS: Our AI-based predictive model was able to identify patients with a predominantly intermediate risk for prostate cancer likely to benefit from short-term ADT. (Supported by a grant [U10CA180822] from NRG Oncology Statistical and Data Management Center, a grant [UG1CA189867] from NCI Community Oncology Research Program, a grant [U10CA180868] from NRG Oncology Operations, and a grant [U24CA196067] from NRG Specimen Bank from the National Cancer Institute and by Artera, Inc. ClinicalTrials.gov numbers NCT00767286, NCT00002597, NCT00769548, NCT00005044, and NCT00033631.)