Diagnosis Of Cancer Patients Research Articles

The Value of Elastography in the Detection of Prostate Cancer – Clinical Experience

The aim of this study was to evaluate the efficacy of real-time shear wave elastography (SWE) in prostate cancer diagnosis in patients with elevated prostate-specific antigen values and abnormal results on digital rectal examination. This study included 74 patients (mean age 68.3 years) with suspected prostate cancer – prostate-specific antigen>4 ng/mL and abnormal digital rectal examination. All patients scheduled for transrectal ultrasound biopsy of the prostate underwent standard transrectal ultrasonography and SWE. The reported sensitivity and specificity of SWE in the various studies varied widely, from 43–96% and 33–96%, respectively. This study showed that patients with elevated levels of prostate-specific antigen, abnormal digital rectal examination, and negative SWE may not require a biopsy which could significantly reduce the number of biopsies performed.

B-314 Utility of he4 in differential diagnosis of pleural effusions

Abstract Background The usefulness of tumor markers in the differential diagnosis of cancer in patients with pleural effusions (PE) remains controversial. Few studies have reported the measurement of human epididymal protein 4 (HE4) in pleural fluid. HE4 is a tumor marker associated with different types of cancer. An elevated serum concentration has been observed in ovarian and lung cancers. Other benign pathologies can increase HE4 levels, which can be detect with different laboratory tests identified with adenosine deaminase (ADA), C-reactive protein (CRP), % polynuclear cell count (%PMN) and glomerular filtration rate (GFR) can be used in order to detect possible false positives. The objective of this study was to assess the diagnostic usefulness of HE4 in malignant pleural effusions by comparing HE4 concentrations between benign and malignant samples, while considering the causes of HE4 false positives. Methods HE4, ADA, differential leukocyte count, CRP and GFR concentrations were determined in 238 pleural effusion samples. Diagnostic efficacy analysis using receiver operating curves (ROC) identified the ability of HE4 to detect malignancy, searching for cut-off points with 100% specificity. Results HE4 concentrations showed significant differences (P<0.01) between malignant (median 1065pmol/L) and benign (median 699pmol/L) pleural effusions. Significant differences (P<0.01) were found in HE4 concentrations for gynecological and lung cancer origin (median 7397 pmol/L and 5150 pmol/L respectively) and other malignant pleural effusions (median 1065 pmol/L). Patients with benign diseases with renal failure showed a higher HE4 concentration (median 964pmol/L) than in patients without these pathologies (median 696pmol/L) identified with GFR<30 mL/min. No differences were demonstrated in HE4 concentration levels using ADA, differential leukocyte count or CRP, so only glomerular filtration rate was considered cause of false positives. A sensitivity of 23% was obtained for HE4, with a cut-off point of 3050pmol/L and a specificity of 100% for the whole group. In the potential false positive group, the sensitivity of HE4 was 28% with a cutoff point of 3050 pmol/L with a specificity of 100%. In the group without potential false positives, we obtained a sensitivity of 30% with a specificity of 100% for a cutoff point of 1992pmol/L. When we used a specific cut-off point for each group, we obtained a sensitivity of 38% with a specificity of 100%. Conclusions HE4 levels are higher in malignant pleural effusions compared to other pathologies. HE4 levels allow the identification of malignant pleural effusions with moderate sensitivity and maximum specificity. HE4 levels can differentiate between tumors of gynecological or lung origin and others. Glomerular filtration rate (GFR<30 mL/min) was considered the main cause of false positives. If we identify possible false positives, we can use specific cut-offs and improve sensitivity up to 38% with maximum specificity compared to using a single cut-off for all effusions.

Impact of Medicaid expansion on receipt of pancreatectomy in early-stage pancreatic cancer.

106 Background: Pancreatic cancer is estimated to rank third in cancer-related mortality in 2024 by the American Cancer Society. Despite the proven increase in 5-year survival with pancreatectomy in Early Pancreatic Cancer (EPC), it is nationally underutilized. Medicaid expansion (ME) under the Affordable Care Act is associated with gains in insurance coverage and early cancer diagnosis in patients with pancreatic cancer. However, its impact on the receipt of pancreatectomy in EPC remains unclear. In this study, we looked at the impact of ME on the uptake of pancreatectomy in EPC. Methods: We performed a retrospective observational study using the Surveillance, Epidemiology, and End Results (SEER) database, which included patients diagnosed with EPC (Stage 1 and Stage 2) between 2006 and 2021. Multivariate logistic regression was performed to ascertain the effects of ME on the uptake of pancreatectomy in patients with EPC in states that expanded vs. states that did not, with 2014 as an inflection point for policy implementation. Results: During this study period, 29,384 were diagnosed with EPC, 10,777 patients were diagnosed pre-ME and 18,607 post-ME. The odds of receipt of pancreatectomy for EPC in non-expansion states after 2014 was 20% higher than before 2014. However, this was not statistically significant [AOR – 1.20 (0.98-1.48)]. There was also no significant difference between the odds of receipt of treatment for EPC for ME states before [AOR- 1.27 (1.06-1.51)] and after [AOR-1.21 (1.01-1.44)] 2014. Increasing age, male sex, Black and Hispanic race, having an income lower than $65,000, and living in less populated areas were all associated with lower odds of receipt of pancreatectomy in EPC. Conclusions: ME was not associated with increased uptake of pancreatectomy in EPC. However, prior studies have shown that ME is linked to an earlier stage at pancreatic cancer diagnosis. This suggests that despite earlier diagnosis, other barriers to receiving treatment exist. Future studies are warranted to identify the limitations of policy change to improve outcomes of such aggressive cancer. Logistic regression for receipt of pancreatectomy in early-stage pancreatic cancer. Receipt of Surgical Treatment for Early Pancreatic cancer Adjusted Odds Ratio (95% Confidence Interval) Non- ME States (Pre-Expansion) 1.00 (Reference) Non- ME States (Post -Expansion) 1.20 (0.98-1.48) ME States (Pre-Expansion) 1.27 (1.06-1.51) ME States (Post-Expansion) 1.21 (1.01-1.44) ME- Medicaid expansion.

Improving the diagnosis of cancer in patients with non-site-specific symptoms: an evaluation of the suspicions of cancer service

Improving the diagnosis of cancer in patients with non-site-specific symptoms: an evaluation of the suspicions of cancer service

Cure models, survival probabilities, and solid organ transplantation for patients with colorectal cancer

A previous cancer diagnosis can preclude patients from consideration for solid organ transplantation. Statistical models may improve candidate selection. We fitted statistical cure models and estimated 5-year cancer-specific survival (5yCSS) for colorectal cancer patients in the United States using registry data. The median cure probability at cancer diagnosis for patients in the general population was 0.67. Among 956 colorectal cancer patients who underwent solid organ transplantation, the median time since diagnosis was 6.3 years and the median 5yCSS at transplantation was 0.96. Patients with a 5yCSS below 0.90 had increased posttransplant cancer-specific mortality (hazard ratio 3.31, 95% CI 1.52-7.21). Compared with recently published guidelines, our models suggested shorter wait times for some groups of colorectal cancer patients (eg, stage IIA cancers) and longer wait times for others (stages IIB, IIIB, IIIC, IV). In conclusion, colorectal cancer patients undergoing solid organ transplantation had excellent prognoses, reflecting selection incorporating existing guidelines and clinical judgment. Nonetheless, 5yCSS probabilities estimated from cure models offer additional prognostic information for patients considered for transplantation and identify situations where current guidelines might be revised. We developed a web-based tool for clinicians to calculate 5yCSS probabilities for use in transplant evaluation for individual colorectal cancer patients (https://dceg.cancer.gov/tools/risk-assessment/calculator-of-colorectal-cancer-survival-probability).

Cancer in Patients With Incidental Asymmetric Oropharynx Positron Emission Tomography Uptake

Asymmetric oropharynx uptake on positron emission tomography (PET)/computed tomography (CT) is a common incidental finding and often prompts otolaryngology referral to rule out malignancy; however, the true risk of malignancy based on this finding is unknown. To identify the incidence of oropharynx cancer in patients with incidental asymmetric oropharynx PET uptake. In this retrospective cohort study, patients 18 years and older undergoing PET/CT scans at Mayo Clinic between January 2001 and December 2018 were included. Patients with a history or pretest suspicion of oropharynx cancer were excluded. Data were analyzed from March 2021 to December 2023. Blinded radiologic review of imaging studies, including measurement of maximum standardized uptake values (SUVmax) of the ipsilateral side of concern and contralateral side. Retrospective medical record review for associated clinical data. The primary study outcome was the incidence of oropharynx cancer diagnosis in patients with asymmetric oropharynx PET uptake. The primary outcome was formulated before data collection. Of the 1854 patients identified with asymmetric oropharynx PET uptake, 327 (17.6%) met inclusion criteria. Of these, 173 (52.9%) were male, and the median (range) age was 65.0 (24.8-90.7) years. The mean (SD) follow-up interval was 52.1 (43.4) months. A total of 18 of 327 patients (5.5%) were newly diagnosed with oropharynx cancer. The most common diagnosis was squamous cell carcinoma (n = 9), followed by lymphoma (n = 8), and sarcoma (n = 1). Patients with an incidental diagnosis of oropharynx cancer had higher mean (SD) ipsilateral SUVmax (8.7 [3.7] vs 5.3 [1.9]) and SUVmax ratio (3.0 [1.6] vs 1.6 [0.6]) compared with patients with normal examination findings. SUVmax ratio and difference were found to be good discriminators of oropharynx cancer, with areas under the receiver operating characteristic curve of 86.3% (95% CI, 76.4-94.6) and 85.8% (95% CI, 74.8-94.6), respectively. Patients with a new diagnosis of oropharynx cancer were more likely to have a corresponding CT abnormality than those with normal examination findings (6 of 18 [33%] vs 24 of 295 [8.1%]). Patients with concerning lesions on oropharynx palpation by an otolaryngology health care professional were significantly more likely to be diagnosed with oropharynx cancer compared with patients with normal examination findings (odds ratio, 28.4; 95% CI, 6.6-145.8). In this cohort study, while incidental asymmetric oropharynx PET uptake was common, a new diagnosis of oropharynx cancer was not and potentially results in a large volume of unnecessary referrals and work-up. Using SUVmax ratio, SUVmax difference, and CT correlation may increase the benefit of referral. Patients with a palpable oropharynx lesion and asymmetric oropharynx PET uptake should undergo confirmatory biopsy.

An Effective Lung Cancer Diagnosis Model Using the CNN Algorithm

The disease known as lung cancer is a serious condition that may be deadly if it is not diagnosed at an early stage. The diagnosis of lung cancer has to be improved, and there is a need for a cost-effective and user-friendly system that leverages state-of-the-art data science technology. This would help simplify operations, save time and money, and improve diagnosis. This research suggests the use of a convolutional neural network (CNN) architecture for the purpose of categorizing three unique histopathological pictures, namely benign, adenocarcinoma, and squamous cell carcinoma. The purpose of this study is to apply the CNN model to properly classify these three kinds of cancers and to compare the accuracy of the CNN model to the accuracy of other techniques that have been employed in investigations that are comparable to this one. The CNN model was not used in any of the preceding research for the purpose of categorizing these particular histopathological pictures; hence, the relevance of this work cannot be overstated. It is possible to get more positive treatment results by correctly classifying malignant tumors as early as possible. In training, the CNN model obtained an accuracy of 96.11%, and in validation, it earned an accuracy of 97.2%. The suggested method has the potential to improve lung cancer diagnosis in patients by classifying them into subgroups according to the symptoms they exhibit. This approach to machine learning, which makes use of the random forest technique, has the potential to reduce the amount of time, resources, and labor required. Utilizing the CNN model to categorize histopathological pictures may, ultimately, improve the diagnostic accuracy of lung cancer and save lives by allowing early disease identification.

Heart failure in patients with congenital heart disease after a cancer diagnosis.

Individuals with congenital heart disease (CHD) are at an increased risk for cancer. As cancer survival rates improve, the prevalence of late side effects, such as heart failure (HF), is becoming more evident. This study aims to evaluate the risk of developing HF following a cancer diagnosis in patients with CHD, compared with those without CHD and with CHD patients who do not have cancer. CHD patients (n=69799) and randomly selected non-CHD controls (n=650406), born in Sweden between 1952 and 2017, were identified from the Swedish National Health Registers and Total Population Register (excluding those with syndromes and transplant recipients). CHD patients who developed cancer (n=1309) were propensity score-matched with non-CHD patients who developed cancer (n=9425), resulting in a cohort of 1232 CHD patients with cancer and 2602 non-CHD controls with cancer (after exclusion of individuals with HF prior to cancer diagnosis). In a separate analysis, CHD patients with cancer were propensity score-matched with CHD patients without cancer (n=68490). A total of 1233 CHD patients with cancer and 2257 CHD patients without cancer were included in the study. Among CHD patients with cancer, 73 (5.9%) developed HF during a mean follow-up time of 8.5±8.7. Comparatively, in the propensity-matched control population, 29 (1.1%) non-CHD cancer patients (mean follow-up time of 7.3±7.5) and 101 (4.5%) CHD patients without cancer (mean follow-up time of 9.9±9.2) developed HF. CHD patients exhibited a significantly higher risk of HF post-cancer diagnosis compared with the non-CHD control group [hazard ratio (HR) 4.39, 95% confidence interval (CI) 2.83-6.81], after adjusting for age at cancer diagnosis and comorbidities. In the analysis between CHD patients with cancer and those without cancer, the results indicated a significantly higher risk of developing HF in CHD patients with cancer (HR 1.53, 95% CI 1.13-2.07). CHD patients face a more than four-fold increased risk of developing HF after a cancer diagnosis compared with cancer patients without CHD. Among CHD patients, the risk of HF is only modestly higher for those with cancer than for those without cancer. This suggests that the increased HF risk in CHD patients with cancer, relative to non-CHD cancer patients, may be more attributable to CHD itself than to cancer treatment-related side effects.

Symptom Burden and Time from Symptom Onset to Cancer Diagnosis in Patients with Early-Onset Colorectal Cancer: A Multicenter Retrospective Analysis.

Background: The incidence of colorectal cancer (CRC) is decreasing in individuals >50 years due to organised screening but has increased for younger individuals. We characterized symptoms and their timing before diagnosis in young individuals. Methods: We identified all patients diagnosed with CRC between 1990-2017 in British Columbia, Canada. Individuals <50 years (n = 2544, EoCRC) and a matched cohort >50 (n = 2570, LoCRC) underwent chart review to identify CRC related symptoms at diagnosis and determine time from symptom onset to diagnosis. Results: Across all stages of CRC, EoCRC presented with significantly more symptoms than LoCRC (Stage 1 mean ± SD: 1.3 ± 0.9 vs. 0.7 ± 0.9, p = 0.0008; Stage 4: 3.3 ± 1.5 vs. 2.3 ± 1.7, p < 0.0001). Greater symptom burden at diagnosis was associated with worse survival in both EoCRC (p < 0.0001) and LoCRC (p < 0.0001). When controlling for cancer stage, both age (HR 0.87, 95% CI 0.8-1.0, p = 0.008) and increasing symptom number were independently associated with worse survival in multivariate models. Conclusions: Patients with EoCRC present with a greater number of symptoms of longer duration than LoCRC; however, time from patient reported symptom onset was not associated with worse outcomes.

Abstract SY02-03: Stochastic modeling of clonal evolution in carcinogenesis

Abstract In order to develop strategies that can detect cancer earlier, we need to better understand the dynamics of cancer evolution during the human lifetime. Starting from gestation, this includes measuring both the timing of early somatic mutations that lead to clonal mosaicism as well as the growth rates of mutated clones that carry higher potential for malignant transformation. Continuous observation of this evolving clonal composition across a lifetime is not feasible, therefore mathematical models are needed to integrate data from longitudinal and cross-sectional samples and infer these dynamics. Stochastic models of clonal evolution offer such a framework and provide a means for predicting individual clone trajectories into the future. Furthermore, if measurements of evolution are to be utilized clinically for early detection and patient risk stratification, faster methods to apply these models to data are required. To this end, we derived methods using coalescent theory for single-cell DNA sequencing data that enable instantaneous estimation of the growth rate of a clone along with its confidence intervals. Our tool is available in an open source R package, cloneRate, and provides the first method for constructing valid confidence intervals of growth rates analytically without having to rely on Bayesian inference techniques and complex simulations. When applying our methods to recent datasets derived from normal and neoplastic human blood cells, we quantified increased fitness effects of multi-hit driver mutations and found that higher initial clone growth rates led to decreased time to cancer diagnosis in patients. We can also use these models to estimate other important biological parameters that are difficult to measure in vivo such as bounds for total number of hematopoietic stem cells and expansion rates in early development. Ultimately, the ability to easily and quickly parameterize clonal dynamics in individual patients will benefit future early detection efforts and screening strategies for many cancer types. Citation Format: Kit Curtius. Stochastic modeling of clonal evolution in carcinogenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY02-03.

Effect of statin treatment on the risk of cancer in patients with heart failure: A target trial emulation study.

A recent observational study suggested statins could reduce cancer diagnosis in patients with heart failure (HF). The findings need to be validated using robust epidemiological methods. This study aimed to evaluate the effect of statin treatment on the risk of cancer in patients with HF. We conducted two target trial emulations using primary care data from IQVIA Medical Research Database-UK (2000 to 2019) with a clone-censor-weight design. The first emulated trial addressed the treatment initiation effect: initiating within 1 year versus not initiating a statin after the HF diagnosis. The second emulated trial addressed the cumulative exposure effect: continuing a statin for ≤3 years, 3-6 years, and >6 years after initiation. The study outcomes were any incident cancer and site-specific cancer diagnoses. Weighted pooled logistic regression models were used to estimate 10-year risk ratios (RR). 95% confidence intervals (CIs) were estimated using non-parametric bootstrapping. The first emulated trial showed that, compared to no statin, statins did not reduce the cancer risk in patients with HF (RR, 1.05; 95% CI, 0.94-1.15). The second emulated trial showed that, compared to treatment ≤3 years, statins with longer durations did not reduce the cancer risk (3-6 years: RR, 0.94; 95% CI, 0.70-1.33. >6 years: RR, 0.97; 95% CI, 0.79-1.26). No significant risk difference was observed on any site-specific cancer diagnoses. The results from the target trial emulations suggest that statin treatment is not associated with cancer risk in patients with HF.

Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI-RADS v2.1 Score ≥3.

For patients with PI-RADS v2.1 ≥ 3, prostate biopsy is strongly recommended. Due to the unsatisfactory positive rate of biopsy, improvements in clinically significant prostate cancer (csPCa) risk assessments are required. To develop and validate machine learning (ML) models based on clinical and imaging parameters for csPCa detection in patients with PI-RADS v2.1 ≥ 3. Retrospective. One thousand eighty-three patients with PI-RADS v2.1 ≥ 3, randomly split into training (70%, N = 759) and validation (30%, N = 324) datasets, and 147 patients enrolled prospectively for testing. 3.0 T scanners/T2-weighted fast spin echo sequence and DWI with diffusion-weighted single-shot gradient echo planar imaging sequence. The factors evaluated for csPCa detection were age, prostate specific antigen, prostate volume, and the diameter and location of the index lesion, PI-RADSv2.1. Five ML models for csPCa detection were developed: logistic regression (LR), extreme gradient boosting, random forest (RF), decision tree, and support vector machines. The csPCa was defined as Gleason grade ≥2. Univariable and multivariable LR analyses to identify parameters associated with csPCa. Area under the receiver operating characteristic curve (AUC), Brier score, and DeLong test were used to assess and compare the csPCa diagnostic performance with the LR model. The significance level was defined as 0.05. The RF model exhibited the highest AUC (0.880-0.904) and lowest Brier score (0.125-0.133) among the ML models in the validation and testing cohorts, however, there was no difference when compared to the LR model (P = 0.453 and 0.548). The sensitivity and negative predictive values in the validation and testing cohorts were 93.8%-97.6% and 82.7%-95.1%, respectively, at a threshold of 0.450 (99% sensitivity of the RF model). The RF model might help for assessing the risk of csPCa and preventing overdiagnosis and unnecessary biopsy for men with PI-RADSv2.1 ≥ 3. 3 TECHNICAL EFFICACY: Stage 2.

Multi-DNA-Modified Double-Network Hydrogel with Customized Microstructure: A Novel System for Living Circulating Tumor Cells Capture and Real-Time Detection.

The precise and effective isolation of living circulating tumor cells (CTCs) from peripheral blood, followed by their real-time monitoring, is crucial for diagnosing cancer patients. In this study, a cell-imprinted double-network (DN) hydrogel modified with circular multi-DNA (CMD), coined the CMD-imprinted hydrogel with fixed cells as templates (CMD-CIDH), was developed. The hydrogel featured a customized surface for proficient capture of viable CTCs and in situ real-time fluorescent detection without subsequent release. The customized surface, constructed using polyacrylamide/chitosan DN hydrogel as the matrix on the cell template, had a dense network structure, thereby ensuring excellent stability and a low degradation rate. Optimal capture efficiencies, recorded at 93 ± 3% for MCF-7 cells and 90 ± 2% for Hela cells, were achieved by grafting the CMD and adjusting the nodule size on the customized surface. The capture efficiency remained significantly high at 67 ± 11% in simulated breast cancer patient experiments even at a minimal concentration of 5 cells mL-1. Furthermore, CMD grafted onto the surface produced a potent fluorescence signature, enabling in situ real-time fluorescent detection of the target cell's growth state even in complex environments. The customized surface is highly efficient for screening CTCs in peripheral blood and has promising potential for setting up the CTCs culture.

FedCSCD-GAN: A secure and collaborative framework for clinical cancer diagnosis via optimized federated learning and GAN

Digital technologies present unrivaled opportunities to improve healthcare services worldwide. Medical devices and hospitals are now using innovative techniques to diagnose cancer patients. Despite the vast amount of data generated, stored, and communicated to the cloud and edge devices, patient data privacy remains a crucial concern. Federated learning (FL) is a revolutionary distributed learning method with significant potential in medical data processing. However, data privacy, data quality, and model performance issues can make it challenging to develop a resilient model. As a solution to the above-mentioned challenges, a secure and collaborative FedCSCD-GAN framework is proposed for clinical cancer diagnosis under the federated learning and GAN optimization principle. By leveraging the collective intelligence of distributed data sources, this framework seeks to improve cancer diagnosis accuracy while maintaining appropriate security measures for sensitive patient data. In the proposed system, the quasi-identifiers (QIden) are identifiedas independent QIden attributes in health data, while the others areclassified as confidential information (CI). Consequently, to enhance security and privacy f- differential privacy anonymization is performed on the QIden attributes, and the resulting data is mixed with the CI attribute. Using anonymized data, the Cramer GAN was trained using Cramer distance for efficiency, and privacy was assessed. Notably, the suggested architecture obtains diagnosis accuracy of 97.80 % for lung cancer, 96.95 % for prostate cancer, and 97 % for breast cancer. Based on the experimental analysis, the proposed architecture detects cancer accurately and addresses security and collaboration issues. This paradigm has the potential to transform healthcare and improve patient outcomes globally.

A Retrospective Audit of the Triage Process Introduced for Breast Referrals Received During the Covid-19 Pandemic

PurposeDue to restrictions on breast clinic appointments during the Covid-19 pandemic, a triage process was introduced for new patient referrals. The robustness of this process was examined by analysing the incidence of cancer diagnosis and wait times to treatment. MethodsPatients were triaged by secondary care consultant surgeons to an urgent appointment if they had high-risk symptoms based on prespecified guidelines eg, a lump or previous cancer. Those with non-urgent symptoms were seen on a deferred basis. A retrospective audit of patients referred between March 23 and July 20, 2020 was performed, to investigate incidence of cancer, concordance of primary and secondary care diagnosis, and the wait times to first appointment. ResultsMost patients with breast-related symptoms received a face-to-face appointment (69%) with a Primary Care Physician (PCP) or Nurse Practitioner (NP), with 544 (31%) having a telephone PCP/NP appointment. Of 2023 patients, 1461 were triaged by the receiving breast unit to an urgent appointment, 461 to a deferred appointment and 101 to a breast pain telephone clinic. A diagnosis of breast cancer was made in 111/1461 (7.6%), 5/461 (1.1%) and 0% in these triaged groups respectively, and the median wait time to first appointment was 14 days (range 1-94), 32 days (range 6-114) and 21 days (range 10-52, P < .001). ConclusionThe one-stop triage process was safe, with statistically fewer cancer diagnoses in patients allocated a deferred appointment, at a rate similar to that seen in a screening population.

Mental health and quality of life following breast cancer diagnosis in patients seen at a tertiary care hospital in Nairobi, Kenya: A qualitative study.

Mental health challenges are common following cancer diagnosis, negatively impacting treatment and quality of life for breast cancer (BC) patients. This pilot study provides an understanding of the impacts of BC diagnosis and care experiences on the mental health of patients seen at the Aga Khan University Hospital in Nairobi, Kenya. We conducted 40 in-depth interviews, including 10 women with newly diagnosed BC, 10 women with metastatic BC, 10 family members and 10 healthcare professionals. Data were transcribed, translated into English as needed and coded using Dedoose software. Following BC diagnosis, it was reported that patients faced various physical, social, psychological and spiritual factors affecting their mental health and quality of life. Our interviews with each group indicated that BC patients experienced feelings of stress, anxiety and depression related to treatments and accompanying side effects. Disclosure concerns, financial impacts, relationship strain and negative outlooks on life were common among BC patients. The findings indicate that BC diagnosis and care experiences influence mental health in this population. With this basis, understanding and addressing the mental health challenges of BC patients is crucial to improve mental health and quality of life.

Detection of Circulating Tumor DNA After Stereotactic Ablative Radiotherapy in Patients With Unbiopsied Lung Tumors (SABR-DETECT)

For patients with stage I/IIA non–small-cell lung cancer (NSCLC), surgical resection is the standard treatment. However, some of these patients are not candidates for surgery or refuse a surgical option. Definitive stereotactic ablative radiotherapy (SABR) is a standard approach in these patients. Approximately 15% of patients undergoing SABR for localized NSCLC will experience a recurrence within 2 years. Furthermore, many of these patients are deemed appropriate for SABR without a tissue diagnosis, based on the likelihood of malignancy which can be calculated by validated models. A liquid biopsy, detecting ctDNA, would be useful in early detection of recurrences, and documenting a cancer diagnosis in patients without a biopsy. This is a multi-institutional study enrolling patients with suspected stage I/IIA NSCLC and a pretreatment likelihood of malignancy of ≥60% using the validated models for patients without a tissue diagnosis, in cohort 1 (n = 45). The second cohort will consist of biopsied patients (n = 30-60). SABR will be delivered as per risk-adapted protocol. Plasma will be collected for ctDNA analysis prior to the first fraction of SABR, 24 to 72 hours after first fraction, and at 3, 6, 9, 12, 18, and 24-months. The patients will be followed up with imaging at 3, 6, 9, 12, 18, and 24-months. The primary objective is to assess whether a cancer detection liquid biopsy platform can predict recurrence of NSCLC. The secondary objectives are to assess the impact of SABR on detection rates of ctDNA in patients undergoing SABR and to correlate ctDNA positivity and pretreatment probability of malignancy (NCT05921474).

"There's So Much More Support We Could Have Provided": Child Life Specialists' Stories of the Challenges Working in Adult Oncology.

A cancer diagnosis in patients who are parents of minor children is uniquely stressful for both parents and children. Children need developmentally appropriate information and support to help reduce their fears and worries. Child life specialists (CLSs) are health professionals who work in pediatric environments to support children and families with the stress and uncertainty of illnesses. Increasingly, CLSs have been called upon to support children of patients in adult clinical environments. Our objective was to elucidate CLS caregiving narratives related to working with children of adult cancer patients. We used narrative inquiry to interview four CLSs working in adult oncology. Canadian CLSs who have experience providing care for children and families affected by parental cancer were recruited via convenience sampling. We used narrative analysis methods that included multiple close reads of the data, generating narrative themes, and noting conflicts or tensions in the data. CLSs' caregiving stories often highlighted the complexities of working in an adult oncology environment. Their narratives included challenges in providing optimal care to the children, including family-level barriers (such as parental wishes to withhold information from their children) and systemic barriers (such as late referrals and limited options for bereavement support). CLS participants identified several challenges of working with families in adult oncology. The CLSs highlighted a desire for additional institutional support for children of adult oncology patients and for themselves working in these environments in order to achieve what they believed to be optimal care.

Abstract 12984: Impact of Cardio-Ankle Vascular Index on New Cancer Diagnosis in Patients With Coronary Artery Disease

Introduction: Cardiovascular risk factors are associated with increased risk of future cancer. However, the relationship between quantitative parameters of atherosclerosis and the risk of future cancer is unclear. Here we investigated the association between cardio-ankle vascular index (CAVI), an indicator of arterial stiffness, and future new cancer diagnosis in patients with coronary artery disease. Methods: This was a prospective observational study which enrolled consecutive 1122 patients with coronary artery disease, excluding patients with atrial fibrillation or dialysis. According to the receiver operating characteristic curve analysis, the cut-off value of CAVI in predicting new cancer diagnosis was 8.70. We divided patients into two groups: the high-CAVI group (CAVI ≥ 8.70, n = 578, 51.6%) and the low-CAVI group (CAVI &lt; 8.70, n = 544, 48.4%). We compared the patients’ characteristics and followed the incidence of new cancer diagnosis. Results: The high-CAVI group, as compared with the low-CAVI group, were older (72.3 vs. 64.0 years, P &lt; 0.001) and had higher prevalence of diabetes mellitus (53.8 vs. 45.6%, P = 0.006), chronic kidney disease (47.1 vs. 32.5%, P &lt; 0.001) and anemia (46.0 vs. 32.9%, P &lt; 0.001). In contrast, there was no difference in the prevalence of smoking, hypertension, dyslipidemia, heart failure and history of malignancies between two groups. In the follow up period (mean of 2182 days), there were 141 new cancer diagnosis. The cumulative incidence of new cancer diagnosis was significantly higher in the high-CAVI group than in the low-CAVI group ( P = 0.007). In the multivariable Cox proportional hazard analysis after adjusting for confounding factors, CAVI was found to be an independent predictor of new cancer diagnosis (hazard ratio 1.51, 95% confidence interval 1.05-2.17, P = 0.022). Conclusions: High CAVI is associated with the risk of future cancer in patients with coronary artery disease.

Rates of high-risk screening prior to a breast cancer diagnosis in patients under age 40

BackgroundNCCN Guidelines recommend screening young women with an increased breast cancer risk (>20 ​% lifetime risk). We sought to evaluate our institutional rates of high-risk screening in young breast cancer patients prior to their diagnoses." MethodsA single-institution retrospective review (2013–2018) was performed investigating risk scores (Tyrer-Cuzick model) and characteristics of breast cancer patients (age <40 ​y) prior to diagnosis. Results92 breast cancer patients age <40 ​y were identified (average age 34.5). Only 3.3 ​% (n ​= ​3) underwent appropriate screening, despite 35.8 ​% meeting high-risk criteria. Nearly all patients underwent genetic testing (98.9 ​%) with pathogenic mutations identified in 36.5 ​%, including 15.3 ​% with BRCA1/2 mutations. ConclusionsThis analysis highlights a significant discrepancy between those meeting criteria for high-risk screening and those who underwent appropriate screening. We identified that this cohort carries significant genetic burden. Future analysis should investigate these findings on a broader scale and strategies to improve screening.