Intervention For Cancer Survivors Research Articles

Characteristics of Orthodontic Treatment in Cancer Survivors: A Systematic Review.

Background: Survival rates of cancer patients have increased globally and across age groups. Challenges arising from craniofacial growth-development disturbances and dental abnormalities might warrant modifications to standard orthodontic pathways of care. Objective: The aim of this study was to systematically summarize and critically assess the available literature regarding the characteristics of orthodontic treatment in cancer survivors. Materials and Methods: A systematic search was conducted in seven databases for studies on malignant tumor survivors having undergone orthodontic intervention with fixed appliances following cancer treatment up to August 2023. The outcomes of interest included quantitative data regarding various characteristics of orthodontic treatment and the post-treatment period. The risk of bias was assessed individually with the Newcastle-Ottawa scale. Results: Out of 347 records, 4 cohort studies were eventually included in the qualitative synthesis. Leukemia was the most common malignancy type, with treatment involving mainly chemotherapy and/or radiotherapy. The duration of orthodontic treatment in cancer survivors varied. Occlusal results, quality of life, and satisfaction were comparable to healthy peers. However, in some survivors' groups, treatment was shorter and the final results were compromised. Root resorption and oral mucositis were reported among the treated cancer survivors. Reduced occlusal outcome stability during the retention period was also reported. Conclusions: Overall, the duration of orthodontic treatment varied among cancer survivors. The occlusal results achieved were similar to those of their healthy peers, though potentially less stable. Patient-reported outcomes did not differ significantly between cancer survivors and healthy individuals treated orthodontically.

Abstract PO1-17-05: Real-world effectiveness of palbociclib plus aromatase inhibitors (AI) in metastatic breast cancer patients with cardiovascular diseases

Abstract Background Breast cancer survivors are at risk for mortality from cardiovascular diseases (CVD). CVD and their treatments can impact breast cancer treatment selection and clinical outcomes. A cyclin dependent kinase 4/6 inhibitor (CDK4/6i) combined with endocrine therapy (ET) is more effective than ET alone for hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2) metastatic breast cancer (MBC). CDK4/6i plus ET is now the standard of care in the first-line setting for HR+/HER2 MBC. However, data on the effectiveness of CDK4/6i in MBC patients with CVD are limited. We compared overall survival (OS) and real-world progression-free survival (rwPFS) of palbociclib plus AI (PAL+AI) vs AI alone in HR+/HER2 MBC patients with CVD in routine US clinical practices. Methods The Flatiron Health longitudinal database contains electronic health records from >280 cancer clinics, representing >3 million actively treated cancer patients in the US. Using the Flatiron database, we conducted a retrospective analysis of 469 patients with HR+/HER2 MBC and CVD who started PAL+AI or AI as first-line therapy between February 2015 and March 2020. CVD prior to the initiation of PAL+AI or AI were identified based on their definitions within the National Cancer Institute-Comorbidity Index (NCI-CI), including myocardial infarction, congestive heart failure, peripheral vascular diseases, and cerebrovascular diseases. Patients were assessed from start of PAL+AI or AI to September 30, 2020 (data cutoff date), death, or last visit, whichever came first. OS was defined as months from start of PAL+AI or AI to death. rwPFS was defined as months from start of PAL+AI or AI to death or disease progression, evaluated based on clinical assessment or radiographic scan/tissue biopsy. Stabilized inverse probability treatment weighting (sIPTW) as primary analysis was used to balance baseline demographics and clinical characteristics. Cox proportional-hazards models were used to estimate the relative effectiveness of PAL+AI vs AI alone. Results Of the 469 eligible patients, 160 (34.1%) were treated with PAL+AI and 309 (65.9%) were treated with AI alone. Compared with AI-alone patients, those treated with PAL+AI were younger and were more likely to have de novo MBC, ≥2 metastatic sites, and lung/liver involvement. After sIPTW, patient characteristics were generally balanced. After sIPTW, median OS (95% confidence interval [CI]) was 40.7 months (30.956.0) in PAL+AI patients and 26.5 months (23.337.3) in AI patients (hazard ratio [HR]=0.732, 95% CI=0.5370.997, p=0.0476). Median rwPFS (95% CI) was 20.0 months (11.7–27.5) in PAL+AI patients and 12.5 months (9.718.3) in AI patients (HR=0.679, 95% CI=0.5120.900, p=0.0070). Consistent results were observed with multivariate Cox proportional-hazards models as sensitivity analysis. See Table for baseline patient characteristics and outcome results. Conclusions First-line PAL in combination with AI is associated with prolonged OS and rwPFS in patients with HR+/HER2 MBC and CVD in a real-world setting compared with AI alone. Further studies with larger cohorts and comprehensive assessments of comorbidities are needed to provide additional evidence of outcomes and safety of CDK4/6i plus AI for MBC patients with various comorbid conditions in routine clinical practice. Citation Format: Adam Brufsky, Xianchen Liu, Benjamin Li, Lynn McRoy, Connie Chen, Doris Makari, Rachel Layman, Hope Rugo. Real-world effectiveness of palbociclib plus aromatase inhibitors (AI) in metastatic breast cancer patients with cardiovascular diseases [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-17-05.

Digital Pathology for Better Clinical Practice.

(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.

Comparing symptom clusters in cancer survivors by cancer diagnosis: A latent class profile analysis

PurposeResearch on symptom clusters in oncology is progressing, but knowledge gaps remain. One question is whether the number and types of symptom subgroups (i.e., latent classes) differ based on cancer diagnosis. The purpose of this study was to: (1) identify and compare latent class subgroups based on four highly prevalent symptoms (pain, fatigue, sleep disturbance, and depression), and (2) examine the differences in sociodemographic and clinical factors in the identified latent classes across the seven cancer types (i.e., prostate, non-small cell lung, non-Hodgkin’s lymphoma, breast, uterine, cervical, and colorectal cancer).MethodsThis study is a cross-sectional secondary analysis of data obtained from the My-Health study in partnership with four Surveillance, Epidemiology, and End Results (SEER) cancer registries located in California (two), Louisiana, and New Jersey. The sample included 4,762 cancer survivors 6-13 months following diagnosis of one of the seven cancer types mentioned. Latent class profile analysis was used.ResultsSubjects were primarily young (59% age 21-64 years), Caucasian (41%), married/cohabitating (58%) and unemployed (55%). The number and types of symptom subgroups varied across these seven cancer populations: four-subgroups were the common in prostate, lung, non-Hodgkin’s lymphoma, and breast cancer survivors. Unmarried, low education, and unemployment status were associated with high risk of symptom burden across the cancer types.ConclusionIdentifying symptom subgroups by cancer diagnosis has the potential to develop innovative and effective targeted interventions in cancer survivors. Further research is needed to establish extensive knowledge in symptom clustering between treatment regimens, and short-term and long-term cancer survivors.

Adaptation and study protocol for harvest for health together Arizona: A mentored community garden intervention for survivors of cancer

BackgroundCurrent health behavior recommendations for skin cancer prevention, treatment, and survivorship are the same for survivors of other cancers; they include eating a healthy diet, being physically active, maintaining a healthy weight, and minimizing ultraviolet (U.V.) exposure. Few interventions exist to support health behaviors beyond U.V. exposure. We adapted Harvest for Health, a home-based mentored gardening intervention for cancer survivors, for implementation in Arizona as a community-based intervention. MethodsStakeholder-informed adaptations for Harvest for Health Together Arizona (H4H2-AZ) included updating intervention materials to be relevant to the arid desert environment, emphasizing the importance of sun safety in cancer survivorship, and shifting from a home-based to a community-based delivery model. Participants will be enrolled in cohorts aligned with growing seasons (e.g., spring, monsoon, fall) and matched to an individual 30 ft2 community garden plot for two growing seasons (6 months). Original intervention components retained are: 1) Master Gardeners deliver the intervention providing one-to-one mentorship and 2) gardening materials and supplies provided. This pilot six-month single-arm intervention will determine feasibility, acceptability, and appropriateness of an evidence-based adapted mentored community gardening intervention for survivors of skin cancer as primary outcomes. Secondary outcomes are to explore the effects on cancer preventive health behaviors and health-related quality of life. DiscussionThis pilot single-arm intervention will determine feasibility, acceptability, and appropriateness of an evidence-based adapted mentored community gardening intervention for survivors of skin cancer. If successful, the intervention could be widely implemented throughout existing Master Gardener programs and community garden networks for survivors of other cancers. Trial registrationClinicalTrials.gov identifier: NCT05648604. Trial registered on December 13, 2022.

Abstract 5015: Genomic profiling of colorectal cancer - insights from liquid biopsy comparisons between U.S. and China cohorts

Abstract Background: Molecular characteristics play a pivotal role in cancer diagnosis, treatment selection, and disease monitoring across various tumor types. While previous research has elucidated the molecular classification of colorectal cancer using tissue NGS, limited investigation has explored the molecular profile of colorectal cancer through liquid biopsy, especially across diverse human races. This study presents a comprehensive genomic profiling analysis of colorectal cancer patients, using a globally harmonized liquid biopsy assay to compare patient cohorts from both the U.S. and China. Methods: The prospective study is part of Predicine’s Phoenix Program, a global molecular biomarker screening initiative across multiple solid tumors. At present, the study has enrolled 57 patients in the U.S. and 62 patients in China, all presenting with advanced colorectal cancer. A 10ml blood sample was collected from each patient and tested using PredicineCARE, an NGS-based liquid biopsy assay, to profile somatic mutations, copy number variations, and gene fusions among these patients. Results: The assay, validated in both the U.S. and China using the same reference materials, achieved a LOD of 0.25% mutation allele frequency, with a positive predictive value exceeding 99%. Subsequently, the assay was applied to profile molecular aberrations in colorectal patients in both the U.S. and China. Among U.S. patients, the most commonly altered genes were APC (60%), KRAS (56%), TP53 (54%), MYC (25%), PIK3CA (16%), and EGFR (14%). In Chinese patients, the predominant altered genes were TP53 (48%), APC (42%), KRAS (32%), GNAS (21%), EGFR (16%), and PIK3CA (11%). The prevalence of GNAS variations was significantly higher in China than in the U.S. (p < 0.05), while the prevalence of APC (p < 0.05), KRAS (p < 0.01), and MYC (p < 0.001) variations was significantly higher in the U.S. than in China. Conclusions: This study reveals the extensive mutational landscape in advanced colorectal cancer patients through liquid biopsy. Distinct prevalence patterns in certain genes between the U.S. and China cohorts offer novel biomarkers for clinical diagnosis and provide insights for targeted therapy mechanism studies. Citation Format: Haoran Tang, Cancan Jia, Feng Xie, Yue Zhang, Xiaoxi Dong, Yong Huang, Shidong Jia. Genomic profiling of colorectal cancer - insights from liquid biopsy comparisons between U.S. and China cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5015.

Abstract 7566: Identification of cancer subtypes with a ctDNA-based targeted methylation assay

Abstract Introduction: Identifying cancer subtypes is necessary for cancer diagnosis, prognosis determination, and treatment selection. Furthermore, as transformation between subtypes is increasingly recognized as a key resistance mechanism to targeted therapies, serial subtype reassessment is likely to gain adoption. Cancer subtypes have traditionally been determined by pathologists based on histology; more recently, molecular subtyping has been performed using IHC, RNAseq, or assays that detect genetic alterations. However, these methods have significant limitations, including tissue biopsy requirement (IHC and RNAseq), low discriminative resolution for distinct transcriptional programs (IHC and mutation detection), and poor reproducibility and feasibility (RNAseq). The GRAIL plasma-only, ctDNA-based targeted methylation platform is a robust, biopsy-free, scalable assay that can distinguish cancer methylation patterns between different cancer signal origins through the use of a proprietary classifier. Here, we explore the GRAIL platform’s potential to detect finer-scale differences in cancer biology by developing classification algorithms for subtyping of three common cancer types. Methods: As part of the Circulating Cell-free Genome Atlas (NCT02889978) and STRIVE (NCT03085888) studies, clinical data were recorded and plasma samples were collected, accessioned, stored, and processed through GRAIL’s targeted methylation assay from 3,989 cancer and 6,013 non-cancer participants. We developed algorithms to predict cancer status and subtype for breast (triple negative breast cancer [TNBC] model; 531 cancer training participants), lung (lung histology model; 334 cancer training participants), and head and neck (HPV model; 3090 cancer training participants) cancers. Dimensionality reduction of methylation data was performed to illustrate subtype separation within these cancer types. Performance of these three algorithms was assessed on a held-out cohort of cancer samples (184 breast, 241 lung, 67 head and neck) with detectable ctDNA. Results: The lung histology model correctly classified 95% (105/111) of adenocarcinomas, 88% (68/77) of squamous cell carcinomas, and 94% (59/63) of lung neuroendocrine carcinomas and tumors. The TNBC model correctly classified 84% (58/69) of TNBCs and 82% (94/115) of non-TNBCs. The HPV model correctly identified 98% (48/49) of HPV-positive head and neck cancers, and 89% (16/18) of HPV-negative head and neck cancers. Conclusions: GRAIL’s proprietary ctDNA-based targeted methylation platform demonstrates the ability to accurately predict cancer subtypes in multiple cancers using only a plasma sample without the need for tumor biopsy. Future efforts will be directed towards generalizing the GRAIL subtyping method to additional cohorts and cancer types. Citation Format: Tracy Nance, Timothy Shaver, Yifan Zhou, Margaret Antonio, Yinjie Gao, Jonathan Heiss, Robert Calef, Joseph Hiatt, Oliver Venn, Joerg Bredno, John Beausang, Lisa Newman, Charles Swanton, Chun Zhang. Identification of cancer subtypes with a ctDNA-based targeted methylation assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7566.

Accelerated Aging in Cancer Survivors: Cellular Senescence, Frailty, and Possible Opportunities for Interventions.

The population of cancer survivors has markedly increased due to the rapid improvements in cancer treatment. However, cancer survivors experience accelerated aging, which leads to chronic diseases and other age-related conditions, such as frailty. Those conditions may persist years after cancer diagnosis and treatment. Cellular senescence, a hallmark of aging, is one of the mechanisms that contribute to accelerated aging in cancer survivors. Several aging measures, including measures based on clinical markers and biomarkers, have been proposed to estimate the aging process, and some of them have shown associations with mortality and frailty in cancer survivors. Several anti-aging interventions, including lifestyle changes and anti-aging drugs, have been proposed. Future research, particularly in large-scale studies, is needed to determine the efficiency of these aging measures and anti-aging interventions before considering their application in clinics. This review focuses on the mechanisms of cellular senescence and accelerated aging in cancer survivors, assessment of the aging process using clinical markers and biomarkers, and the high prevalence of frailty in that population, as well as possible opportunities for anti-aging interventions. A deeper understanding of aging measures and anti-aging interventions in cancer survivors will contribute to the development of effective strategies to mitigate accelerated aging in cancer survivors and improve their quality of life.

Medication-based Comorbidity Measures and Prostate Cancer Treatment Selection

IntroductionWe aimed to assess the association between comorbidities and prostate cancer management. Patients and methodsWe studied 12,603 South Australian men diagnosed with prostate cancer between 2003 and 2019. Comorbidity was measured one year prior to prostate cancer diagnosis using a medication-based comorbidity index (Rx-Risk). Binomial logistic regression analyses were used to assess the association between comorbidities and primary treatment selection (active surveillance, radical prostatectomy (RP), external beam radiotherapy (EBRT) with or without androgen deprivation therapy (ADT), brachytherapy, ADT alone, and watchful waiting (WW)). Certain common comorbidities within Rx-Risk (cardiac disorders, diabetes, chronic airway diseases, depression and anxiety, thrombosis, and chronic pain) were also assessed. All models were adjusted for sociodemographic and tumor characteristics. ResultsLikelihood of receiving RP was lower among men with Rx-Risk score ≥3 (odds ratio (OR) 0.62, 95%CI:0.56-0.69) and Rx-Risk 2 (OR 0.80, 95%CI:0.70-0.92) compared with no comorbidity (Rx-Risk ≤0). Men with high comorbidity (Rx-Risk ≥3) were more likely to have received ADT alone (OR 1.76, 95%CI:1.40-2.21), EBRT (OR 1.30, 95%CI:1.17-1.45) or WW (OR 1.49, 95%CI:1.19-1.88) compared with Rx-Risk ≤0. Pre-existing cardiac and respiratory disorders, thrombosis, diabetes, depression and anxiety, and chronic pain were associated with lower likelihood of selecting RP and higher likelihood of EBRT (except chronic airway disease) or WW (except diabetes and depression and anxiety). Cardiac disorders and thrombosis were associated with higher likelihood of selecting ADT alone. Furthermore, age had greater effect on treatment choice than the level of comorbidity. ConclusionHigh comorbidity burden was associated with primary treatment choice, with significantly less RP and more EBRT, WW and ADT alone among men with higher levels of comorbidity. Each of the individual comorbid conditions also influenced treatment selection.

A multisite initiative to increase medical oncologists’ utilization of clinical pathways in the selection of systemic cancer treatment.

575 Background: The Swedish Cancer Institute (SCI) recognizes that quality cancer care is a systemwide commitment. In 2020, SCI implemented ClinicalPath (formerly Via Oncology). The ClinicalPath tool assists in the selection of systemic treatment protocols. The protocols balance considerations of clinical efficacy, safety, toxicities, and cost. National utilization rate for ClinicalPath ranges between 50-70%. In 2021, ClinicalPath monthly utilization by SCI medical oncologists was 56%. This initiative aimed to increase utilization of ClinicalPath by SCI Medical Oncologists, across the three main campuses, to above 70% by the end of 2022. Methods: The Plan Do Study Act framework was used. Utilization was defined as accessing the ClinicalPath tool. Utilization data was abstracted from an Epic Workbench Report that was filtered to reflect practicing SCI medical oncologists and the 25 diagnoses included in ClinicalPath. An introduction email and meeting request was sent to eight Medical Directors. A fishbone diagram was used to identify the potential causes of low utilization. PDSA 1 interventions included 1:1 meeting with each Medical Director to validate baseline data for cascading to their oncologists and encourage engagement. PDSA 2 included monthly “Quality Messages” with oncologists’ monthly utilization rate. In addition, a public recognition of “Most Improved Utilization” from Q1 to Q2 was done by the SCI Executive Medical Director. PDSA 3 focused on wide dissemination of the initiative through presentations that included a link to a “Tips & Tricks for ClinicalPath” video at SCI executive and department meetings. Public recognition of “Top Performers” from Q3 was published in the SCI newsletter. Results: The process measure of 1:1 meeting with Medical Directors was achieved at 100%. During PDSA 1 the outcome measure of monthly utilization rates improved to 71%. The 2nd PDSA cycle yielded a utilization rate of 84%. The 3rd PDSA cycle monthly utilization rate by the end of 2022 was 86%. At the most recent tracking into 2023, the utilization rate showed sustainability with achieved rates of 83%, 80%, 80% for Jan, Feb, March. Conclusions: Engaging the SCI Medical Directors and sharing individual performance data with the medical oncologists was a simple intervention yet yielded a significant improvement in their ClinicalPath utilization rates. Public recognition, along with addressing common barriers through education resulted in further improvement. This approach serves as a model for increasing utilization of a point of care clinical decision tool.

The prevalence and risk factors for physical impairments in Chinese post-cancer treated breast cancer survivors: a 4 years’ cross-sectional study at a single center

The incidence of breast cancer in China was 19.2% in 2018, with a five-year survival rate of up to 80%. The impairments that may result from breast cancer treatment, such as lymphedema, pain, and symptoms related to nerve damage, could have long-term side effects. Its prevalence and symptom profile have been commonly reported in various countries, but such data are rarely available for China. Physical function was assessed in 138 breast cancer survivors (BCSs) in the study. The prevalence of lymphedema (65.9%) was higher than that of pain (31.2%), shoulder range of motion (ROM) restriction (20.3%), grip strength restriction (GSR) (21.7%) and paresthesia (11.6%). These impairments mainly appeared within 28 months after breast cancer diagnosis, but could happen in 10 years. Carcinoma in situ and radiotherapy (RT) were related to the occurrence of lymphedema (respectively B = -1.8, p = 0.003; B = 1.3, p = 0.001). RT and delayed rehabilitation time (DRT) may increase the severity of lymphedema (respectively p = 0.003, p = 0.010). Breast conserving surgery (B = -2.1, p = 0.002) and the occurrence of AWS (B = 3.1, p = 0.006) were related to the occurrence of pain. The occurrence of brachial plexus injury (BPI) (B = 3.1, p < 0.001) and pain (B = 1.9, p = 0.002) improved the occurrence of shoulder ROM restriction. The occurrence of BPI (B = 3.6, p < 0.001) improved the occurrence of GSR. The occurrence of pain (B = 2.1, p = 0.001) improved the occurrence of paresthesia. These findings prompt us to further investigate the actual rehabilitation needs of survivors and the specific barriers to rehabilitation in the following research.

Incidence of Major Depression, Suicidal Ideation, and Mental Health Treatment Amongst Cancer Survivors

Receiving a cancer diagnosis and undergoing subsequent treatments can result in a significant psychological burden for cancer patients. However, there is conflicting literature on the incidence of major depression in cancer patients compared to patients without cancer. The purpose of this study was to investigate and further clarify the incidence of major depression, associated treatments, and suicidal ideation in cancer survivors compared to a non-cancer cohort. This is a retrospective, population-based study using survey responses from the National Survey on Drug Use and Health collected from January 2015 to December 2019. Survey data sets were queried for all respondents aged 18 years or older who provided a cancer history. Patients with a reported history of cancer ("cancer survivors") were further stratified by whether they reported a "recent" cancer diagnosis within the past 12 months. Survey responses were then evaluated for recent diagnoses of and treatments for major depressive disorder and suicidal ideation. Rates were compared between cancer survivors and participants without cancer using the Pearson χ2 test and multivariable logistic regression models, respectively. Among the 212,411 survey respondents identified, 7,635 (3.6%) reported a cancer history, with 1,486 (0.7%) reporting a recent cancer history. The incidence of major depression was not different between cancer survivors and participants without cancer (9.3% vs. 9.2%; p = 0.762), though the incidence was slightly higher amongst recent cancer survivors (10.0% vs. 9.2%; p = 0.259). Among patients diagnosed with major depression, cancer survivors were significantly more likely to receive treatment for depression (78.6% vs. 60.3%, p<0.001), with 72.6% discussing depressive symptoms with a medical professional and 64.3% receiving prescription medication. Suicidal ideation was significantly lower among cancer survivors (5.1% vs. 6.2%, p<0.001) including recent survivors (5.0% vs. 6.2%, p<0.001). Suicidal ideation was higher in patients with underlying major depression in both cancer survivors and participants without cancer (30.6% vs. 35.6%, p = 0.015). On logistic regression, respondents with underlying depression receiving treatment were more likely to have suicidal ideation (OR: 1.49; p<0.001) while having a cancer diagnosis did not correlate with suicidal ideation (OR: 0.87; p = 0.869). There was no significant overall difference in the incidences of major depression between cancer survivors and patients without cancer. However, one consideration is the under-diagnosis depression among cancer survivors. Symptoms of depression may be overlooked and mistakenly attributed to appropriate grief from a cancer diagnosis. Among patients diagnosed with major depression, cancer survivors were more likely to receive treatment for depression. These results highlight the importance of early depression assessment and treatment for cancer survivors.

Value of biplane transrectal ultrasonography plus micro-flow imaging in preoperative T staging and rectal cancer diagnosis in combination with CEA/CA199 and MRI

BackgroundRectal cancer is one of the most common malignant tumors and has a high incidence rate and fatality rate. Accurate preoperative T staging of rectal cancer is critical for the selection of appropriate rectal cancer treatment. Various pre-operative imaging methods are available, and the identification of the most accurate method for clinical use is essential for patient care. We investigated the value of biplane transrectal ultrasonography (TRUS) combined with MFI in preoperative staging of rectal cancer and explored the value of combining TRUS plus MFI with CEA/CA199 and MRI.MethodsA total of 87 patients from Daping Hospital with rectal cancer who underwent TRUS examination plus MFI were included. Grades of MFI were determined by Alder classification. Among the total patients, 64 underwent MRI and serum CEA/CA199 tests additionally within one week of TRUS. Pathological results were used as the gold standard for cancer staging. Concordance rates between TRUS, MRI, and CEA/CA199 for tumors at different stages were compared.ResultsThere were no significant differences between the Alder classification and pathological T staging. The concordance rate of TRUS and MFI for rectal cancer T staging was 72.4% (K = 0.615, p < 0.001). Serum CEA and CA199 levels were significantly different in tumors at different stages and increased progressively by pathological stage (p < 0.001); the accuracy rate was 71.88% (K = 0.599, p < 0.001), while that of MRI was 51.56% (K = 0.303, p < 0.001), indicating that TRUS had higher consistency in the preoperative T staging of rectal cancer. The combination of TRUS, MRI, and CEA/CA199 yielded an accuracy rate of 90.6%, which was higher than that of any method alone.ConclusionsPreoperative T staging of rectal cancer from biplane TRUS plus MFI was highly consistent with postoperative pathological T staging. TRUS combined with MRI and serum CEA/CA199 had a greater value in the diagnosis of rectal cancer and a higher diagnostic rate than any examination alone.

High-throughput extraction on a dynamic solid phase for low-abundance biomarker isolation from biological samples

Liquid biopsy, in particular circulating tumor DNA (ctDNA) analysis, has paved the way for a new noninvasive approach to cancer diagnosis, treatment selection and follow-up. As a crucial step in the analysis, the extraction of the genetic material from a complex matrix needs to meet specific requirements such as high specificity and low loss of target. Here, we developed a new generation of microfluidic fluidized beds (FBs) that enable the efficient extraction and preconcentration of specific ctDNA sequences from human serum with flow rates up to 15 µL/min. We first demonstrated that implementation of a vibration system inducing flow rate fluctuations combined with a mixture of different bead sizes significantly enhanced bead homogeneity, thereby increasing capture efficiency. Taking advantage of this new generation of high-throughput magnetic FBs, we then developed a new method to selectively capture a double-stranded (dsDNA) BRAF mutated DNA sequence in complex matrices such as patient serum. Finally, as proof of concept, ligation chain reaction (LCR) assays were performed to specifically amplify a mutated BRAF sequence, allowing the detection of concentrations as low as 6 × 104 copies/µL of the mutated DNA sequence in serum.

Interpretable HER2 scoring by evaluating clinical guidelines through a weakly supervised, constrained deep learning approach.

The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection. However, HER2 scoring has notoriously high interobserver variability due to stain variations between centers and the need to estimate visually the staining intensity in specific percentages of tumor area. In this paper, focusing on the interpretability of HER2 scoring by a pathologist, we propose a semi-automatic, two-stage deep learning approach that directly evaluates the clinical HER2 guidelines defined by the American Society of Clinical Oncology/ College of American Pathologists (ASCO/CAP). In the first stage, we segment the invasive tumor over the user-indicated Region of Interest (ROI). Then, in the second stage, we classify the tumor tissue into four HER2 classes. For the classification stage, we use weakly supervised, constrained optimization to find a model that classifies cancerous patches such that the tumor surface percentage meets the guidelines specification of each HER2 class. We end the second stage by freezing the model and refining its output logits in a supervised way to all slide labels in the training set. To ensure the quality of our dataset's labels, we conducted a multi-pathologist HER2 scoring consensus. For the assessment of doubtful cases where no consensus was found, our model can help by interpreting its HER2 class percentages output. We achieve a performance of 0.78 in F1-score on the test set while keeping our model interpretable for the pathologist, hopefully contributing to interpretable AI models in digital pathology.

Which symptom to address in psychological treatment for cancer survivors when fear of cancer recurrence, depressive symptoms, and cancer-related fatigue co-occur? Exploring the level of agreement between three systematic approaches to select the focus of treatment.

To investigate the extent to which three systematic approaches for prioritizing symptoms lead to similar treatment advices in cancer survivors with co-occurring fear of cancer recurrence, depressive symptoms, and/or cancer-related fatigue. Psychological treatment advices were was based on three approaches: patient preference, symptom severity, and temporal precedence of symptoms based on ecological momentary assessments. The level of agreement was calculated according to the Kappa statistic. Overall, we found limited agreement between the three approaches. Pairwise comparison showed moderate agreement between patient preference and symptom severity. Most patients preferred treatment for fatigue. Treatment for fear of cancer recurrence was mostly indicated when based on symptom severity. Agreement between temporal precedence and the other approaches was slight. A clear treatment advice based on temporal precedence was possible in 57% of cases. In cases where it was possible, all symptoms were about equally likely to be indicated. The three approaches lead to different treatment advices. Future research should determine how the approaches are related to treatment outcome. We propose to discuss the results of each approach in a shared decision-making process to make a well-informed and personalized decision with regard to which symptom to target in psychological treatment. This study contributes to the development of systematic approaches for selecting the focus of psychologicaltreatment in cancer survivors with co-occurring symptoms by providing and comparing three different systematic approaches for prioritizing symptoms.

Chapter 4: CKD treatment in cancer survivors, from Clinical Practice Guidelines for the Management of Kidney Injury During Anticancer Drug Therapy 2022.

Chronic kidney disease (CKD) is one of the most disabling disorders with significant comorbidity and mortality. Incidence and prevalence of CKD in cancer survivors are remarkably high in both adults and pediatric patients. The reasons for this high incidence/prevalence are multifold but kidney damage by cancer itself and cancer treatment (pharmacotherapy/surgery/radiation) are the main reasons. Since cancer survivors commonly have significant comorbidities, risk of cancer recurrence, limited physical function or life expectancy, special attentions should be paid when considering the treatment of CKD and its complications. Especially, shared decision-making should be considered when selecting the renal replacement therapies with as much information/facts/evidence as possible.

Machine Learning and AI in Cancer Prognosis, Prediction, and Treatment Selection: A Critical Approach.

Cancer is a leading cause of morbidity and mortality worldwide. While progress has been made in the diagnosis, prognosis, and treatment of cancer patients, individualized and data-driven care remains a challenge. Artificial intelligence (AI), which is used to predict and automate many cancers, has emerged as a promising option for improving healthcare accuracy and patient outcomes. AI applications in oncology include risk assessment, early diagnosis, patient prognosis estimation, and treatment selection based on deep knowledge. Machine learning (ML), a subset of AI that enables computers to learn from training data, has been highly effective at predicting various types of cancer, including breast, brain, lung, liver, and prostate cancer. In fact, AI and ML have demonstrated greater accuracy in predicting cancer than clinicians. These technologies also have the potential to improve the diagnosis, prognosis, and quality of life of patients with various illnesses, not just cancer. Therefore, it is important to improve current AI and ML technologies and to develop new programs to benefit patients. This article examines the use of AI and ML algorithms in cancer prediction, including their current applications, limitations, and future prospects.

Comprehensive multigene profiling impact on clinical decisions in patients with advanced cancers: A multicenter, retrospective analysis.

e15163 Background: Comprehensive molecular profiling (CMP) via next generation sequencing (NGS) is currently applied in clinical practice and has enabled the detection of biomarkers of response to targeted treatment. Given the lack of the data about optimal range of analyzed alterations, the clinical usefulness of CMP has not been established. To address the challenges in incorporating genomics in treatment of oncology patients, we conducted a retrospective study. Methods: Preliminary analysis of NGS reports and clinical data of patients with advanced solid tumors was performed. CMP was conducted in 261 cancer patients (non-small cell lung cancer - 30,6%, colorectal cancer - 24,8%, pancreatic cancer - 7,4%, breast cancer- 6,2%; 59,3% were female, median number of prior systemic treatment lines was 2 (0-12)). In the present study, tumor molecular profile analysis was performed using 160 - 400 gene NGS panels, containing the majority of clinically significant genes for cancer treatment selection. We assessed the percentage of patients who were recommended to receive molecularly-matched therapy (MMT) after CMP, immunotherapy (IT) distribution of recommended therapies according to ESCAT tiers, median progression-free survival (PFS) – ratio ( = PFS after CMP / PFS before CMP, PFS2/PFS1), median PFS2. Results: MMT after CMP was recommended for 55 (21,1%) patients. ESCAT tiers could be assessed in 48 MMT patients (87%). For 31% of patients, administered therapy was considered as ESCAT I tier recommendation (data on mPFS2/1, mPFS2 not available). ESCAT tiers II, III, IV and IT administration were considered in 31, 8, 8 and 22% of patients respectively (detailed data is presented in Table 1). Most commonly altered genes were TP53 (53%), RAS (29%), APC (18%), CDKN2A/B (16%), PIK3CA(14%), NF1 (10%), BRCA1/2 (9%). Positive predictive factors for MMT after CMP were MSI-high status (HR 0,13, 95% CI 0,03 - 0,67), presence of EGFR alteration (HR 0,32, 95% CI 0,12 - 0,86). Presence of RAS mutation was considered a negative predictive factor (HR 2,78, 1,07 - 7,26). Conclusions: Available NGS panels offer a wide range of analyzed alterations that are not feasible in clinical practice. Most of the alterations that can cause impact on treatment plan can be detected with other methods than NGS. Further studies are needed to determine optimal range of alterations depending on tumor site. [Table: see text]

The Impact of Covid-19 Pandemic on The Selection of Prostate Cancer Treatment among Urologist in Indonesia: A Survey Analysis

Abstract&#x0D; Prostate cancer (PCa) is the sixth leading cause of cancer death in men worldwide. Incidence of PCa in Indonesia placed in number 6th, the data from Globocan 2020 also showed that PCa lined up as the highest urological cancer cases in both sexes of the country. The cancer has broad spectrum treatments, the selection of which can be determined by risk classification. However, in the setting of the coronavirus disease 2019 (COVID-19) pandemic, health care, including urology services worldwide have been undergone changes particularly in terms of treatment protocol. This study seeks to determine how the COVID-19 pandemic influences the choice of treatment of PCa in Indonesia. This was a cross-sectional study through a questionnaire which was distributed via Survey Monkey (www.surveymonkey.com), a cloud-based online survey. A survey was delivered to all urologists in Indonesia who were registered in each association. A total of 174 urologists completed the questionnaire. Amongst 117 respondents who performed prostate biopsy, 39.2% and 37.5% working in public and private hospital had more than 50% reduction or no prostate biopsy procedure during COVID-19 pandemic. However, only 27.0% deferred prostate biopsy due to COVID-19. During pandemic, 73 (42%) respondents who previously chose radical prostatectomy as their priority for localized PCa, shifted their choice into active surveillance and androgen deprivation therapy (ADT) evenly that made active surveillance as primary choice of treatment in localized cases. Moreover, only 12.1% and 10.3% chose ADT combination therapy (with docetaxel, abiraterone acetate, enzalutamide/apalutamide) as their primary choice of metastatic PCa treatment before and during COVID-19 pandemic. In conclusion, the impact of COVID-19 on PCa were prominent in diagnostic procedure and management of localized or low risk PCa.&#x0D; &#x0D; Keywords: COVID-19, prostate cancer, radical prostatectomy, active surveillance, radiation, androgen deprivation therapy, chemotherapy&#x0D; &#x0D; Abstrak&#x0D; Kanker prostat adalah kanker pada laki-laki dengan angka kematian tertinggi keenam di dunia. Di Indonesia insidens kanker prostat berada di peringkat ke-6 dan merupakan jenis kanker urologi terbanyak berdasarkan data Globocan 2020. Tersedia beragam terapi kanker prostat dan pemilihan terapi berdasarkan klasifikasi risiko tertentu. Pada situasi pandemi coronavirus disease 2019 (COVID-19), fasilitas pelayanan kesehatan di dunia, termasuk layanan urologi, mengalami perubahan terkait protokol tata laksana. Penelitian ini bertujuan untuk mengetahui pengaruh pandemi COVID-19 terhadap pilihan terapi kanker prostat di Indonesia. Penelitian ini menggunakan desain potong-lintang dan data diperoleh dari kuesioner yang didistribusikan melalui Survey Monkey (www.surveymonkey.com), sebuah survei daring berbasis cloud. Survei dikirim kepada seluruh urolog di Indonesia yang terdaftar di tiap asosiasi. Responden adalah 174 urolog yang telah melengkapi kuesioner. Di antara 117 responden yang mengerjakan biopsi prostat, 39,2% yang bekerja di rumah sakit umum dan 37,5% di rumah sakit swasta mengalami pengurangan jumlah prosedur biopsi prostat &gt; 50% atau tidak melakukannya sama sekali. Hanya 27,0% yang menunda biopsi prostat akibat COVID-19. Sebelum pandemi, 73 responden (42%) memilih prostatektomi radikal sebagai prioritas utama untuk kanker prostat lokal, namun selama pandemi pilihan beralih ke surveilans aktif dan terapi deprivasi androgen secara merata, menjadikan surveilans aktif sebagai pilihan utama. Selain itu pada kasus kanker prostat metastasis jumlah responden yang memilih kombinasi terapi deprivasi androgen dengan dosetaksel, abirateron asetat, atau enzalutamid/apalutamid) sebagai pilihan utama hanya 12,1% sebelum dan 10,3% saat pandemi COVID-19. Disimpulkan dampak COVID-19 terlihat lebih nyata pada prosedur diagnostik dan manajemen kanker prostat lokal atau berisiko rendah.&#x0D; &#x0D; Kata kunci: COVID-19, kanker prostat, prostatektomi radikal, surveilans aktif, radiasi, terapi deprivasi androgen, kemoterapi.