Cancer Treatment Decisions Research Articles

The Prognostic Value of Eight Comorbidity Indices in Older Patients with Cancer: The ELCAPA Cohort Study.

Simple SummaryA prognostic assessment is crucial for making cancer treatment decisions. However, the frequent presence of comorbidities makes this assessment particularly challenging in older adults. Many comorbidity indices are available, but none have been developed for older patients with cancer. We assessed the prognostic performance (relative to one-year mortality) of eight comorbidity indices in a cohort of older patients with cancer. All the comorbidity indices were independently associated with 1-year mortality in the whole study population, and had very good discriminant ability. Among patients with metastatic cancer, only CIRS-G was independently associated with 1-year mortality.Background: A prognostic assessment is crucial for making cancer treatment decisions in older patients. We assessed the prognostic performance (relative to one-year mortality) of eight comorbidity indices in a cohort of older patients with cancer. Methods: We studied patients with cancer aged ≥70 included in the Elderly Cancer Patient (ELCAPA) cohort between 2007 and 2010. We assessed seven nonspecific indices (Charlson Comorbidity Index (CCI), three modified versions of the CCI, the Elixhauser Comorbidity Index, the Gagne index, and the Cumulative Illness Rating Scale for Geriatrics (CIRS-G)) and the National Cancer Institute Comorbidity Index. Results: Overall, 510 patients were included. Among patients with nonmetastatic cancer, all the comorbidity indices were independently associated with 1-year mortality (adjusted hazard ratios (aHRs) of 1.44 to 2.51 for one standard deviation increment; p < 0.05 for all) and had very good discriminant ability (Harrell’s C > 0.8 for the eight indices), but were poorly calibrated. Among patients with metastatic cancer, only the CIRS-G was independently associated with 1-year mortality (aHR (95% confidence interval): 1.26 [1.06–1.50]). Discriminant ability was moderate (0.61 to 0.70) for the subsets of patients with metastatic cancer and colorectal cancer. Conclusion: Comorbidity indices had strong prognostic value and discriminative ability for one-year mortality in older patients with nonmetastatic cancer, although calibration was poor. In older patients with metastatic cancer, only the CIRS-G was predictive of one-year mortality.

Improving ovarian cancer treatment decision using a novel risk predictive tool.

Background: As a major component of the tumor tissue, the tumor microenvironment (TME) has been proven to associate with tumor progression and immunotherapy. Ovarian cancer accounts for the highest mortality rate among gynecologic malignancies. Its clinical treatment decision is highly correlated with the prognosis, underscoring the need to evaluate the prognosis and choose the proper clinical treatment through TME information.Method: This study constructs a score with TME information obtained by the CIBERSORT algorithm, which classifies the patients into high and low TMEscore groups with quantified TME infiltration patterns through the PCA algorithm. TMEscore was constructed by TCGA cohort and validated in GEO cohort. Univariate and multivariate Cox proportional hazards model analyses were used to demonstrate prognostic value of TMEscore in overall and stratified analysis.Result: TMEscore is highly correlated with survival and high TMEscore group has a better prognosis. In order to improve treatment decision, the expression of immune checkpoints, immunophenoscore (IPS) and ESTIMATE score showed a high TMEscore have a better immune microenvironment and respond better to immune checkpoint inhibitors (ICIs). Meanwhile, the mutation landscape between TMEscore groups was profiled, and 13 genes were found mutated differently between the two groups. Among them, BRCA1 has more mutations in the high TMEscore group and speculated that high TMEscore patients might be a beneficiary population of PARP inhibitors combined with immunotherapy.Conclusion: TMEscore based on TME with prognostic value and clinical value is proposed for the identification of targets treatment and immunotherapy strategies for ovarian cancer.

Age-Independent Preoperative Chemosensitivity and 5-Year Outcome Determined by Combined 70- and 80-Gene Signature in a Prospective Trial in Early-Stage Breast Cancer

BackgroundThe Neoadjuvant Breast Symphony Trial (NBRST) demonstrated the 70-gene risk of distant recurrence signature, MammaPrint, and the 80-gene molecular subtyping signature, BluePrint, precisely determined preoperative pathological complete response (pCR) in breast cancer patients. We report 5-year follow-up results in addition to an exploratory analysis by age and menopausal status.MethodsThe observational, prospective NBRST (NCT01479101) included 954 early-stage breast cancer patients aged 18–90 years who received neoadjuvant chemotherapy and had clinical and genomic data available. Chemosensitivity and 5-year distant metastasis-free survival (DMFS) and overall survival (OS) were assessed. In a post hoc subanalysis, results were stratified by age (≤ 50 vs. > 50 years) and menopausal status in patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2−) tumors.ResultsMammaPrint and BluePrint further classified 23% of tumors to a different subtype compared with immunohistochemistry, with more precise correspondence to pCR rates. Five-year DMFS and OS were highest in MammaPrint Low Risk, Luminal A-type and HER2-type tumors, and lowest in MammaPrint High Risk, Luminal B-type and Basal-type tumors. There was no significant difference in chemosensitivity between younger and older patients with Low-Risk (2.2% vs. 3.8%; p = 0.64) or High-Risk tumors (14.5% vs. 11.5%; p = 0.42), or within each BluePrint subtype; this was similar when stratifying by menopausal status. The 5-year outcomes were comparable by age or menopausal status for each molecular subtype.ConclusionIntrinsic preoperative chemosensitivity and long-term outcomes were precisely determined by BluePrint and MammaPrint regardless of patient age, supporting the utility of these assays to inform treatment and surgical decisions in early-stage breast cancer.

Cancer treatment and decision making in individuals with intellectual disabilities: a scoping literature review.

Adults with intellectual disabilities face disparities in receipt of cancer-related care, which could contribute to an increase in the rate of cancer-related deaths in this population. Yet, relatively little is known about the optimal cancer treatment or treatment decision making in adults with intellectual disabilities. This scoping review assessed PubMed and Embase for available literature on the description of cancer treatment and treatment decision making in patients with intellectual disabilities, published in English between Jan 1, 2000, and April 30, 2020. We appraised 90 included articles and extracted quotes addressing aspects related to cancer treatment and treatment decision making in patients with intellectual disabilities. Themes and subcategories were subsequently derived. Our findings revealed that the available literature describes that people with intellectual disabilities tend to have less intensive cancer treatment than generally administered, but with little evidence supporting this approach. This finding indicates that this medically vulnerable patient population needs tailored attention in both cancer care and research. We propose changes to practice and conclude by addressing the urgent need to pay specific attention to this patient population.

Cardio-Oncology Considerations in Oncologic Treatment Decisions.

At JADPRO Live Virtual 2021, presenter Anecita P. Fadol, PhD, FNP-BC, FAANP, FAAN, emphasized the critical role advanced practitioners play in the identification, monitoring, and management of the cardiac complications of cancer therapy. Dr. Fadol's presentation discussed identification of the most common cardiotoxicities associated with cancer therapy, clinical considerations related to common oncologic treatments with potential cardiotoxicity that may impact cancer treatment decisions, and the management of common cardiovascular issues in patients with cancer.

Comprehensive Evaluation of Machine Learning Models and Gene Expression Signatures for Prostate Cancer Prognosis Using Large Population Cohorts.

This systematic evaluation of 15 machine learning algorithms and 30 published gene expression signatures for the prognosis of prostate cancer will assist clinical decision-making.

Unravelling Prostate Cancer Heterogeneity Using Spatial Approaches to Lipidomics and Transcriptomics.

Simple SummaryProstate cancer is a heterogenous disease in terms of disease aggressiveness and therapy response, leading to dilemmas in treatment decisions. This heterogeneity reflects the multifocal nature of prostate cancer and its diversity in cellular and molecular composition, necessitating spatial molecular approaches. Here in view of the emerging importance of rewired lipid metabolism as a source of biomarkers and therapeutic targets for prostate cancer, we highlight recent advancements in technologies that enable the spatial mapping of lipids and related metabolic pathways associated with prostate cancer development and progression. We also evaluate their potential for future implementation in treatment decision-making in the clinical management of prostate cancer. Due to advances in the detection and management of prostate cancer over the past 20 years, most cases of localised disease are now potentially curable by surgery or radiotherapy, or amenable to active surveillance without treatment. However, this has given rise to a new dilemma for disease management; the inability to distinguish indolent from lethal, aggressive forms of prostate cancer, leading to substantial overtreatment of some patients and delayed intervention for others. Driving this uncertainty is the critical deficit of novel targets for systemic therapy and of validated biomarkers that can inform treatment decision-making and to select and monitor therapy. In part, this lack of progress reflects the inherent challenge of undertaking target and biomarker discovery in clinical prostate tumours, which are cellularly heterogeneous and multifocal, necessitating the use of spatial analytical approaches. In this review, the principles of mass spectrometry-based lipid imaging and complementary gene-based spatial omics technologies, their application to prostate cancer and recent advancements in these technologies are considered. We put in perspective studies that describe spatially-resolved lipid maps and metabolic genes that are associated with prostate tumours compared to benign tissue and increased risk of disease progression, with the aim of evaluating the future implementation of spatial lipidomics and complementary transcriptomics for prognostication, target identification and treatment decision-making for prostate cancer.

Cancer treatment decisions for people living with dementia: Experiences of family carers, a qualitative interview study.

BackgroundAs the UK population ages, the prevalence of both dementia and cancer will increase. Family carers of people with dementia who are subsequently diagnosed with cancer are often involved in treatment decisions about cancer. These decisions are uniquely challenging.ObjectivesTo explore the experience of carers involved in cancer treatment decisions for people with dementia.DesignA cross‐sectional qualitative interview study with inductive thematic analysis.Setting and ParticipantsSixteen carers of people with dementia were identified via Primary Care Research Networks and the Join Dementia Research database.ResultsThree main themes were derived: ‘already at breaking point’, which describes the extreme strain that carers were already under when the cancer diagnosis was made; ‘maintaining the status quo’, which describes how despite the gravity of a cancer diagnosis, avoiding further dementia‐related deterioration was of prime importance; and ‘LPA’, which explores the benefits and frustrations of the use of lasting powers of attorney.DiscussionCurrent services are ill‐equipped to deal with people who have a combination of dementia and cancer. Proxy decisions about cancer care are made in the context of carer stress and exhaustion, which is exacerbated by shortcomings in service provision.ConclusionsAs the prevalence of comorbid cancer and dementia rises, there is an urgent need to improve services that support carers with proxy health care decision‐making.Patient or Public ContributionThe study design was codeveloped with a local dementia‐specific patient and public involvement (PPI) group. A project‐specific PPI group was formed with support from the Alzheimer's Society Research Partnership scheme to provide further bespoke input.

Using clinical decision support systems in breast cancer treatment: a critical review

Decision-making in breast cancer treatment is a complex process. There is no certainty of the effects of a treatment regimen in a specific patient and the consequences of erroneous decisions can be serious or even fatal for the patient. Clinical decision support systems (CDSSs) are technology aids that have been progressively introduced in clinical practice to reduce decision errors and improve the quality of clinical decisions.This article presents a critical review of the empirical literature on the use of CDSSs in breast cancer treatment decision-making. Three articles were included and two salient challenges identified in the design and research of CDSSs. First, there is a lack of standardisation in the tumour and patient factors and the health goals used to predict the benefit of different treatment options, as well as in the methods used for the evaluation of these. Second, the design of CDSSs follows a biomedical, disease-focused approach to healthcare, and this reductionist approach also prevails in the related scholarly literature.

Nanomaterial based analytical methods for breast cancer biomarker detection

Female breast cancer is the leading cause of global cancer incidence and the fifth leading cause of cancer mortality worldwide in 2020. Breast cancer can be categorized into different subtypes according to the expression of biomarkers such as estrogen receptors (ER), progesterone receptors (PR) and human epidermal growth factor receptor 2 (HER2). The analysis of these biomarkers is also indispensable for systemic treatment decisions in breast cancer. In this review, we summarized recent progress for the detection of breast cancer biomarkers in blood utilizing nanomaterials. The attractive physical, chemical, optical and electronic properties of various nanomaterials facilitated the detection of these biomarkers and improved the performance of the detection. The detection of biomarkers in blood is relatively non-invasive and can provide useful biological information that is complementary to imaging examination and immunohistochemistry.

Abstract P4-12-12: Assessing the impact of the COVID-19 pandemic on cancer treatment decision-making and care experiences

Abstract BACKGROUND: While the COVID-19 pandemic has reshaped how oncology is practiced, we sought to understand itseffects on treatment decision-making and care experiences amongst cancer patients at the Tom BakerCancer Centre in Calgary, Canada. METHODS: A 24 item, cross-sectional survey was developed based on literature review and iterative feedback fromoncology physicians, nurses, and a patient advisor. Survey domains included fear of COVID-19 andperceived risk, uptake of COVID-19 public health measures, cancer treatment decision-making duringthe pandemic, and cancer care experiences during the pandemic. Demographic, cancer and treatment-related information was obtained from the electronic medical record for patients who consented andcompleted the survey. In the first quarter of 2021, 161 patients accrued including 44 breast cancerpatients. The cohort characteristics and survey responses were summarized using descriptive statistics. RESULTS: For the 44 participants with breast cancer, all were female and the median age was 59 years (range 35-83 years). Our breast cancer cohort was almost evenly split between those with stage I-III (45.5%) andthose with metastatic disease (54.5%). Time since diagnosis was as follows: less than 1 year (17patients), 1-3 years (10 patients), 3-5 years (5 patients), and more than 5 years (9 patients). Treatmentsreceived since declaration of the pandemic included: surgery (21 patients), radiation (17 patients),chemotherapy (25 patients), endocrine therapy (25 patients), and other systemic therapies such as boneand anti-HER2 agents (15 patients). Just over half of the participants (54.5%) agreed or strongly agreedthat they were at increased risk of contracting COVID19; however, fewer patients expressed beinguncomfortable thinking about COVID-19 (45.4%), afraid of COVID-19 (38.6%), or fearful of dying fromCOVID19 (31.8%). The vast majority (&amp;gt;93%) of patients followed public health recommendations formitigating the risk of contracting COVID-19 (i.e. masking, frequent hand washing/sanitization, and socialdistancing) and 70.4% expressed a willingness to receive the vaccine when available. Of therespondents, 19 had undergone testing for COVID-19 at least once and 3 tested positive. Only 2 patientsreported that their surgical course was altered due to the pandemic and no patients declinedtreatments or perceived delays or modifications in therapies otherwise. Of 25 breast participants whohad experienced a cancer-related telehealth appointment during the pandemic, 21 (84%) agreed orstrongly agreed with being satisfied with the encounter. CONCLUSION: The COVID-19 pandemic caused minimal perceived disruption to care amongst a small cohort of breastcancer patients being treated at our centre. While experience with a cancer-related telehealthappointment was not universal, our findings support acceptability of its use. Citation Format: Noura Alsafar, Desiree Hao, Nimira Alimohamed, Sunil Samnani, Sasha Lupichuk. Assessing the impact of the COVID-19 pandemic on cancer treatment decision-making and care experiences [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-12-12.

Abstract P4-11-02: Prevalence and impact of fertility concerns in young women with breast cancer

Abstract Introduction: Breast cancer treatments can impair fertility via direct gonadotoxicity (chemotherapy) as well as by introducing delays in childbearing that allow natural ovarian aging. Guidelines strongly recommend fertility counseling and consideration of fertility preservation techniques for premenopausal women who have not completed their desired childbearing at the time of cancer diagnosis. Prior studies have identified high rates of fertility concern but relatively low rates of fertility counseling and use of fertility preservation techniques. We sought to investigate rates of fertility counseling, use of fertility preservation techniques, and how fertility concerns impact cancer treatment decisions in a modern cohort of patients with breast cancer at a large academic medical center in the United States. Methods: All patients seen at Mayo Clinic Rochester with a new diagnosis (within the year prior) of stage 0-4 breast cancer were invited (by mail or in person) to participate in the Mayo Clinic Breast Registry. After informed consent, participants were asked to complete a baseline survey and annual follow-up surveys. On baseline and one-year surveys, patients were queried about desire for future children and fertility concerns. Nurse chart abstraction was used to collect information about tumor subtype, stage, and treatments received. We examined survey data from women diagnosed under the age of 50 who expressed an interest in having future biological children on either the baseline or year 1 survey between February 2015 and October 2020. Descriptive statistics were used to summarize the degree of fertility concern in this population, the impact of that concern on cancer treatment decisions, and steps taken to preserve fertility. Results: Between February 2015 and October 2020, 865 women under age 50 at diagnosis consented to the registry. Of these women, 627 completed a baseline and/or 1-year survey and 100 answered either “yes” or “unsure” to the question: “At the present time, do you wish to have any more biological children in the future?” on one or both surveys. Among the 100 women expressing interest in future child-bearing, 92% were white, 27% had node-positive and one had distant metastatic disease at diagnosis. The age at diagnosis ranged from 19 to 49 years, with a mean age of 33.8 years. Of the 75 who reported a desire for future children at baseline, 28% felt “somewhat concerned” about their future fertility and 40% felt “very concerned.” Of the 70 who reported a desire for future children on the year 1 survey, 17% felt “somewhat concerned” and 59% felt “very concerned.” For those “very concerned” about future fertility at year 1, 65% reported that this concern had a major impact on their treatment decisions. Often, that treatment modification entailed using endocrine therapy for less than 5 years; 52% of those who specified the type of treatment modification they had made indicated this option. Of note, six women who reported no desire for future biological children at baseline were “unsure” at year 1. At year 1, 93% of women recalled a discussion about fertility with their doctor prior to starting treatment, and 49% had taken steps to preserve fertility (32.5% with embryo cryopreservation, 20% with oocyte cryopreservation and 65% with a GnRH agonist; some selected multiple options). Conclusion: We found a reassuringly high rate of patient-reported fertility counseling and use of reproductive endocrinology technologies to preserve fertility in women who reported a desire for additional children at or soon after diagnosis with breast cancer. Consistent with prior studies, fertility concerns frequently impacted breast cancer treatment decisions. It is important to err on the side of inclusivity when providing fertility counseling because desire for fertility can change over time. Citation Format: Samantha Mannion, Alexandra Higgins, Elizabeth A Stewart, Zaraq Khan, Chandra Shenoy, Nicole Larson, Hazel B Nichols, H Irene Su, Ann H Partridge, Fergus J Couch, Janet E Olson, Kathryn Ruddy. Prevalence and impact of fertility concerns in young women with breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-11-02.

MetaMutationalSigs: comparison of mutational signature refitting results made easy.

MotivationThe analysis of mutational signatures is becoming increasingly common in cancer genetics, with emerging implications in cancer evolution, classification, treatment decision and prognosis. Recently, several packages have been developed for mutational signature analysis, with each using different methodology and yielding significantly different results. Because of the non-trivial differences in tools’ refitting results, researchers may desire to survey and compare the available tools, in order to objectively evaluate the results for their specific research question, such as which mutational signatures are prevalent in different cancer types.ResultsDue to the need for effective comparison of refitting mutational signatures, we introduce a user-friendly software that can aggregate and visually present results from different refitting packages.Availability and implementationMetaMutationalSigs is implemented using R and python and is available for installation using Docker and available at: https://github.com/EESI/MetaMutationalSigs.

Impact of Oncotype Dx testing in adjuvant treatment decisions in invasive lobular cancer- A single centre experience

Background: The 21 gene essay (Oncotype Dx) is used to assess the recurrence score (RS) and to decide chemotherapy (CT) benefit in oestrogen receptor (ER) positive and HER2 (Human Epidermal Growth Factor Receptor) negative invasive breast cancer. Majority of the Invasive lobular cancers (ILC) are ER +ve and HER2 negative. We have assessed the use of this test in ILC and its impact on the outcome of adjuvant chemotherapy decisions.

Women's fertility decision-making with a diagnosis of breast cancer: A qualitative evidence synthesis.

To synthesize qualitative evidence of premenopausal women's experiences of fertility decision-making with a diagnosis of breast cancer. Breast cancer is increasingly more common in premenopausal women who may have not yet considered starting a family or have completed their families. Qualitative evidence synthesis guided by Thomas and Harden's three-stage approach to thematic analysis. Twelve electronic databases were searched: CINAHL, Embase, Pubmed, Proquest, PsychINFO, Lenus, Scopus, Web of Science, Rian.ie, Medline, EThOS e-theses online and DART Europe. No year limit was set. The 'Enhancing transparency in reporting the synthesis of qualitative research guidelines' (ENTREQ) statement was followed. Fifteen qualitative studies were included in the synthesis. Seven review findings under four major themes were identified: (1) first comes survival, (2) making decisions 'under the gun', (3) health-care professionals should not make assumptions and (4) we want accurate, detailed information and we want it early. High confidence in six of the review findings was agreed. Most women experienced rushed fertility preservation decision-making at a time when they also faced cancer treatment decisions. Women want detailed, clear information on fertility preservation early after their diagnosis.

Elaboration of Multiparametric MRI-Based Radiomics Signature for the Preoperative Quantitative Identification of the Histological Grade in Patients With Non-Small-Cell Lung Cancer.

The histological grading plays an essential role in the treatment decision of lung cancer. Detected tumors are usually biopsied to confirm histologic grade. How to use MRI extracted radiomics features for accurately grading lung cancer is still challenging. To examine the diagnostic utility of multiparametric MRI radiomics and clinical factors for grading non-small-cell lung cancer (NSCLC). Retrospective. A total of 148 patients (25.7% female) with postoperative pathologically confirmed NSCLC and divided into the training cohort (N=110) and the validation cohort (N=38). A 1.5 T; single-shot turbo spin-echo (TSE), T2-weighted imaging (T2WI), and integrated shimming-echo planar imaging (ISHIM-EPI) diffusion-weighted imaging (DWI). A total of 2775 radiomics features were extracted from carcinomatous regions of interest on T2WI, DWI, and the apparent diffusion coefficient (ADC) maps. The five optimal features were selected by using the Student' s t-test, the least absolute shrinkage and selection operator (LASSO) and stepwise regression. The Radscore combined with clinical factors, which selected by univariate and multivariate analyses, to develop a radiomics-clinical nomogram. Its performance was evaluated in the training cohort and the validation cohort. The potential clinical usefulness was analyzed by the receiver operating characteristic curve (ROC), area under the curve (AUC), and the Hosmer-Lemeshow test. Student's t-test, univariate analyses, multivariate analyses, LASSO, ROC, AUC, and the Hosmer-Lemeshow test. P < 0.05 was considered statistically significant. Favorable discrimination performance was obtained for five optimal features (out of the 2775 features), using the training cohorts (AUC 0.761) and validation cohorts (AUC 0.753). In addition, the radiomics-clinical nomogram significantly improved the ability to identify histological grades in the training cohort (AUC 0.814) and the validation cohort (AUC 0.767). The radiomics-clinical nomogram based on multiparametric MRI might have the potential to distinguish the histological grade of NSCLC. 3 TECHNICAL EFFICACY: Stage 2.

Genomic Alterations to Guide Treatment Selection in Metastatic Prostate Cancer.

Treatment options for men with metastatic prostate cancer have greatly expanded in the last decade. Androgen receptor pathway inhibitors, taxane cytotoxic therapy, poly(ADP-ribose) polymerase inhibitors, and radionuclide theranostics against prostate-specific membrane antigen have collectively contributed to incremental improvements in both quality and longevity of life for patients with metastatic castration-resistant prostate cancer (mCRPC). Despite these successes, few studies inform on optimal therapy selection and sequencing across this crowded treatment landscape. Genomic analysis of both tissue and liquid biopsy specimens shows promise in bridging this practice gap, with alterations in several key prostate cancer driver genes demonstrating clear associations with clinical outcomes, as well as informing use of novel precision medicine targeted therapies. In this review, we evaluate the current evidence of genomic alterations in various oncogenic signaling pathways as clinical biomarkers in mCRPC, focusing on correlative studies that analyzed outcomes based on findings in plasma cell-free DNA. We highlight the pitfalls of interpreting genomic findings in samples with substandard tumor content, and suggest pathologic and disease factors to consider when embarking upon tumor genotyping to guide treatment decisions in metastatic prostate cancer. As access to life-prolonging therapies improves, and barriers to cost-effective genotyping and reliable data interpretation are overcome, we anticipate that predictive and prognostic biomarkers that inform on disease biology, drug sensitivity, and therapy resistance will inevitably be integrated into the routine care of patients with metastatic prostate cancer.

MiNuGAN: Dual Segmentation of Mitoses and Nuclei Using Conditional GANs on Multi-center Breast H&E Images

Breast cancer is the second most commonly diagnosed type of cancer among women as of 2021. Grading of histopathological images is used to guide breast cancer treatment decisions and a critical component of this is a mitotic score, which is related to tumor aggressiveness. Manual mitosis counting is an extremely tedious manual task, but automated approaches can be used to overcome inefficiency and subjectivity. In this paper, we propose an automatic mitosis and nuclear segmentation method for a diverse set of H&E breast cancer pathology images. The method is based on a conditional generative adversarial network to segment both mitoses and nuclei at the same time. Architecture optimizations are investigated, including hyper parameters and the addition of a focal loss. The accuracy of the proposed method is investigated using images from multiple centers and scanners, including TUPAC16, ICPR14 and ICPR12 datasets. In TUPAC16, we use 618 carefully annotated images of size 256×256 scanned at 40×. TUPAC16 is used to train the model, and segmentation performance is measured on the test set for both nuclei and mitoses. Results on 200 held-out testing images from the TUPAC16 dataset were mean DSC = 0.784 and 0.721 for nuclear and mitosis, respectively. On 202 ICPR12 images, mitosis segmentation accuracy had a mean DSC = 0.782, indicating the model generalizes well to unseen datasets. For datasets that had mitosis centroid annotations, which included 200 TUPAC16, 202 ICPR12 and 524 ICPR14, a mean F1-score of 0.854 was found indicating high mitosis detection accuracy.

Social determinants of health and treatment decisions in head and neck cancer.

This study compares select social determinants of health (SDOH) with treatment modality selection and treatment completion in head and neck cancer (HNC) patients, to better understand disparities in health outcomes. A retrospective cohort study of HNC (n=1428) patients was conducted. Demographic and disease-specific variables were recorded, including treatment modality selection and completion. Data were analyzed using two-sample t tests, chi-square, and Fisher's exact tests. Primary language was significantly associated with treatment choice, where non-English speakers were less likely to choose treatment as recommended by the Tumor Board. Lower mean distance from the hospital (37.38 [48.31] vs. 16.92 [19.10], p < 0.0001) and a county-based higher mean percentage of bachelor degree or higher education (42.16 [8.82] vs. 44.95 [6.19], p < 0.0003) were associated with treatment selection. Language, distance from the hospital, and education affected treatment selection in this study and may be useful in understanding how to counsel patients on treatment selection for HNC.

A personalized decision aid for prostate cancer shared decision making

BackgroundA shared decision-making model is preferred for engaging prostate cancer patients in treatment decisions. However, the process of assessing an individual’s preferences and values is challenging and not formalized. The purpose of this study is to develop an automated decision aid for patient-centric treatment decision-making using decision analysis, preference thresholds and value elicitations to maximize the compatibility between a patient’s treatment expectations and outcome.MethodsA template for patient-centric medical decision-making was constructed. The inputs included prostate cancer risk group, pre-treatment health state, treatment alternatives (primarily focused on radiation in this model), side effects (erectile dysfunction, urinary incontinence, nocturia and bowel incontinence), and treatment success (5-year freedom from biochemical failure). A linear additive value function was used to combine the values for each attribute (side effects, success and the alternatives) into a value for all prospects. The patient-reported toxicity probabilities were derived from phase II and III trials. The probabilities are conditioned on the starting state for each of the side effects. Toxicity matrices for erectile dysfunction, urinary incontinence, nocturia and bowel incontinence were created for the treatment alternatives. Toxicity probability thresholds were obtained by identifying the patient’s maximum acceptable threshold for each of the side effects. Results are represented as a visual. R and Rstudio were used to perform analyses, and R Shiny for application creation.ResultsWe developed a web-based decision aid. Based on preliminary use of the application, every treatment alternative could be the best choice for a decision maker with a particular set of preferences. This result implies that no treatment has determinist dominance over the remaining treatments and that a preference-based approach can help patients through their decision-making process, potentially affecting compliance with treatment, tolerance of side effects and satisfaction with the decision.ConclusionsWe present a unique patient-centric prostate cancer treatment decision aid that systematically assesses and incorporates a patient’s preferences and values to rank treatment options by likelihood of achieving the preferred outcome. This application enables the practice and study of personalized medicine. This model can be expanded to include additional inputs, such as genomics, as well as competing, concurrent or sequential therapies.