Decision-making For Cancer Patients Research Articles

Assessment of eHealth literacy to reduce financial toxicity and improve shared decision-making in cancer patients: A cross-sectional study.

This study aimed to investigate the associations between eHealth literacy, preferences for financial decision-making, and financial toxicity (FT) in a sample of Chinese cancer patients. Eligible cancer patients were invited to participate in a cross-sectional survey from January to April 2021. Three measures (eHealth literacy scale, control preference scale, and COST) were used to analyze patients' eHealth literacy, decisional preferences, and FT, respectively. Wilcoxon signed-rank test and Kruskal-Wallis H test assessed the differences between population subgroups. Binary logistic and multivariate linear regression models were used to assess the relationships between eHealth literacy, decisional preferences, and FT. A total of 590 cancer patients completed the questionnaire. We found that high FT was associated with poor ECOG performance, severe cancer stage, and longer cancer duration. Patients who preferred to adopt collaborative attitude toward decision-making showed a significantly higher eHealth literacy. However, there was an inverse relationship between eHealth literacy and a patient-driven attitude toward decision-making in female cancer patients. Regression analysis indicated that patients who were highly educated and actively employed might report a higher eHealth literacy. A significant relationship was found between high eHealth literacy and low FT. However, this relationship became insignificant when the background characteristics of cancer patients were taken into account. A relationship between enhanced eHealth literacy, preference for collaborative decision-making, and low risk of FT is identified. Interventions to improve patients' ability to use quality and reliable web-based information on cancer care should be encouraged.

Retrospective analysis of PSMA PET/CT thyroid incidental uptake in adults: incidence, diagnosis, and treatment/outcome in a tertiary cancer referral center and University Medical Center.

A prostate-specific membrane antigen (PSMA) thyroid incidentaloma (PTI) is an unexpected, PSMA-avid thyroid lesion, newly detected during the investigation of an unrelated condition using PSMA PET/CT. The aim of this study is to examine the incidence and clinical significance of PTI and the associated management strategies since the implementation of the PSMA PET/CT scan. This study involves a retrospective cohort study of 61 PTI cases depicted on PSMA PET/CT scans performed between January 2016 and July 2021, almost exclusively for (re)staging prostate cancer. The medical records of the included cases were retrospectively reviewed and data of the PSMA PET/CT scans, primary malignancy, thyroid diagnostics, treatment, and follow-up were collected. PTI was reported in 1.1% of the patients who underwent oncologic PSMA PET/CT scans included in this study. Two PTI cases had a histologically proven thyroid cancer: one a benign thyroid lesion and one a metastasis of a renal cell carcinoma. In none of the cases in whom any form of further thyroid workup was withheld, the PTI became clinically relevant during follow-up (median 1.8years (1.1-3.3)). Six patients (10%) died due to their primary cancer. The incidence of thyroid incidentalomas on PSMA PET/CT was low (1.1%) in this large, two-center experience. Less than half of the PTI cases were analyzed and the risk of malignancy, despite being low, was not negligible. The clinical outcome was good using a standard diagnostic workup for PTI, while the prognosis of the patient was determined by the primary malignancy. The consideration to analyze and treat PTI cases should be part of the shared decision-making in cancer patients.

Machine learning prediction of COVID-19 mortality in cancer patients.

1558 Background: COVID-19 is a challenge for clinical decision-making in cancer patients and the allocation of healthcare resources. An accurate prognosis prediction to effectively triage patients is needed, especially in the community oncology practice. Methods:Nationwide cohort from Oncoclínicas Brazil was used to validate previously developed multivariable logistic regression (mLR) model (Ferrari et al, JCO GO 2021) and to construct a machine learning Random Forest (RF) algorithm as predictor of 30-day mortality after SARS-CoV-2 detection by RT-PCR in cancer patients diagnosed in an outpatient setting. To find the most important baseline clinical determinants of early COVID-19-related death via Gini index, a RF with 100,000 trees was trained in 75% of the dataset, and the performance was assessed in the remaining 25%. We then compared the accuracy of different models in terms of sensitivity, specificity and area under the receiver operating characteristics curves (AUC). Results:From March to December 2020, 533 patients with COVID-19 were prospectively registered in the database. Median age was 60 years (19-93) and 67% were female. Most frequent cancers were breast in 34%, hematological in 16%, and gastrointestinal in 15%. Comorbidities were common (52%), as was current/former smoking history (17%). Most patients were on active systemic therapy or radiotherapy (84%) in the advanced or metastatic disease setting (55%). The overall mortality rate was 15% (CI95% 12%-18%). We validated the original mLR model trained in the first 198 patients: management in a non-curative setting (odds ratio [OR] 3.7), age ≥ 60 years (OR 2.3), and current/former smoking (OR 1.9) were significant predictors of death in the expanded cohort. Presence of comorbidities (OR 1.9) also defined poor outcome in the updated mLR model, which yielded low sensitivity (74%), specificity (68%) and AUC (0.78). With RF modeling, the most significant predictors of 30-day death after COVID-19 (in decreasing order) were older age, treatment of advanced or metastatic disease, tumor type (respiratory tract, brain and unknown primary cancers had higher mortality), COVID-related symptom burden at baseline evaluation and treatment regimen (immunotherapy combinations had higher mortality). The RF model demonstrated high sensitivity (89%), specificity (88%) and AUC (0.96). Conclusions:The results highlight the possibility that machine learning algorithms are able to predict early mortality after COVID-19 in cancer patients with high accuracy. The proposed prediction model may be helpful in the prompt identification of high-risk patients based on clinical features alone, without having to wait for the results of additional tests such as laboratory or radiologic studies. It can also help prioritize medical resources and redefine vaccination strategies. A web-based mortality risk calculator will be created for clinical decision support.

Abstract S09-03: Factors affecting COVID-19 outcomes in cancer patients: A first report from Guy’s Cancer Centre in London

Abstract Background: Current precautionary management decisions being made for cancer patients are based on assumptions supported by limited evidence, based on small case series from China and Italy and larger series from New York and a recent consortium of 900 patients from over 85 hospitals in the USA, Canada, and Spain. Hence, there is insufficient evidence to support clinical decision-making for cancer patients diagnosed with COVID-19 due to the lack of large studies. Methods: We used data from a single large UK Cancer Centre to assess demographic/clinical characteristics of 156 cancer patients with a confirmed COVID-19 diagnosis between 29 February-12 May 2020. Logistic/Cox proportional hazards models were used to identify which demographic and/or clinical characteristics were associated with COVID-19 severity/death. Results: 128 (82%) presented with mild/moderate COVID-19 and 28 (18%) with severe disease. Initial diagnosis of cancer >24m before COVID-19 (OR:1.74 (95%CI: 0.71-4.26)), presenting with fever (6.21 (1.76-21.99)), dyspnea (2.60 (1.00-6.76)), gastrointestinal symptoms (7.38 (2.71-20.16)), or higher levels of CRP (9.43 (0.73-121.12)) were linked with greater COVID-19 severity. During median follow-up of 47d, 34 patients had died of COVID-19 (22%). Asian ethnicity (3.73 (1.28-10.91), palliative treatment (5.74 (1.15-28.79), initial diagnosis of cancer >24m before (2.14 (1.04-4.44), dyspnea (4.94 (1.99-12.25), and increased CRP levels (10.35 (1.05-52.21)) were positively associated with COVID-19 death. An inverse association was observed with increased levels of albumin (0.04 (0.01-0.04). Conclusions: Our analysis of one of the largest single-center series of COVID-19-positive cancer patients to date confirms a similar distribution of age, sex, and comorbidities as reported for other populations. With respect to cancer-specific observations, patients who have lived longer with their cancer were found to be more susceptible to a greater infection severity, possibly reflecting the effect of more advanced malignant disease, as almost half of the severe cohort were on third-line metastatic treatment, or the impact of this infection. The latter was also found to be associated with COVID-19 death in cancer patients, as were Asian ethnicity and palliative treatment. Further validation will be provided from other large case series, as well as from those including longer follow-up, to provide more definite guidance for oncologic care. Citation Format: Beth Russell, Charlotte Moss, Sophie Papa, Sheeba Irshad, Paul Ross, James Spicer, Shahram Kordasti, Danielle Crawley, Harriet Wylie, Fidelma Cahill, Anna Haire, Kamarul Zaki, Fareen Rahman, Ailsa Sita-Lumsden, Debra Josephs, Deborah Enting, Mary Lei, Sharmista Ghosh, Claire Harrison, Angela Swampillai, Richard Sullivan, Anne Rigg, Saoirse Dolly, Mieke Van Hemelrijck, Guy's Cancer Real World Evidence Programme. Factors affecting COVID-19 outcomes in cancer patients: A first report from Guy’s Cancer Centre in London [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr S09-03.

Machine learning defined diagnostic criteria for differentiating pituitary metastasis from autoimmune hypophysitis in patients undergoing immune checkpoint blockade therapy

PurposeNew-onset pituitary gland lesions are observed in up to 18% of cancer patients undergoing treatment with immune checkpoint blockers (ICB). We aimed to develop and validate an imaging-based decision-making algorithm for use by the clinician that helps differentiate pituitary metastasis (PM) from ICB-induced autoimmune hypophysitis (HP). Materials and methodsA systematic search was performed in the MEDLINE and EMBASE databases up to October 2018 to identify studies concerning PM and HP in patients treated with cytotoxic T–lymphocyte–associated protein 4 and programmed cell death (ligand) 1. The reference standard for diagnosis was confirmation by histology or response on follow-up imaging. Patients from included studies were randomly assigned to the training set or the validation set. Using machine learning (random forest tree algorithm) with the most-described six imaging and three clinical features, a multivariable prediction model (the signature) was developed and validated for diagnosing PM. Signature performance was evaluated using area under a receiver operating characteristic curves (AUCs). ResultsOut of 3174 screened articles, 65 were included totalising 122 patients (HP: 60 pts, PM: 62 pts). Complete radiological data were available in 82 pts (Training: 62 pts, Validation: 20 pts). The signature reached an AUC = 0.91 (0.82, 1.00), P < 10−8 in the training set and AUC = 0.94 (0.80, 1.00), P = 0.001 in the validation set. The signature predicted PM in lesions either ≥ 2 cm in size or < 2 cm if associated with heterogeneous contrast enhancement and cavernous extension. ConclusionAn image-based signature was developed with machine learning and validated for differentiating PM from HP. This tool could be used by clinicians for enhanced decision-making in cancer patients undergoing ICB treatment with new-onset, concerning lesions of the pituitary gland.

Fertility decision-making in cancer patients – current status and future directions

ABSTRACTIntroduction: With long-term cancer survivor rates increasing, quality of life, and a pivotal component of it, the ability to procreate are of growing importance. As treatment can compromise fertility, patients need to be informed about the currently available options to preserve it. However, decisional conflict may arise, as decisions have to be made within the short time frame after diagnosis and before treatment.Areas covered: Decisional conflict reflects the personal perception of uncertainty in choosing between different options. It is typical in decision-making in the context of fertility preservation (FP). It comprises factors such as feeling uninformed, lack of clarity regarding personal values, lack of support, and uncertainty and is associated with decisional regret. Research has shown that additional support tools such as decision aids have the potential to increase knowledge and reduce decisional conflict.Expert commentary: Improvement in the availability of and access to adequate and ...

PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data

BackgroundLarge-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy.ResultsWe present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility.ConclusionsPanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org.

Abstract P4-10-07: Genetic predictors of chemotherapy-related amenorrhea

Abstract Background: Chemotherapy-related amenorrhea (CRA) impacts quality of life and reproductive options, and may play a role in treatment decision-making for young breast cancer patients. Although age, increasing doses of alkylating agents, and tamoxifen are known to increase the risk of chemotherapy-related amenorrhea (CRA), it is difficult to predict which women will develop CRA in order to inform fertility preservation and treatment decisions. We sought to investigate whether single nucleotide polymorphisms (SNPs) that have been associated with a younger age at natural menopause and ovarian reserve in non-oncologic populations were predictive of CRA in two large German clinical trials that administered gonadotoxic chemotherapy. Methods: A total of 1322 premenopausal participants under age 50 who enrolled in SUCCESS B (a phase 3 trial of FEC-docetaxel-trastuzumab +/- gemcitabine for high risk early stage breast cancer) or SUCCESS C (a phase 3 trial of FEC-docetaxel-cyclophosphamide vs. docetaxel-cyclophosphamide that also tested the efficacy of a weight loss intervention in early stage breast cancer patients) were eligible for this study. We excluded patients who were receiving ovarian suppression. On these trials, menstrual status was self-reported as amenorrheic or not every three months after chemotherapy. Bloods were stored and patients provided consent for DNA analysis. We genotyped nine candidate SNPs in six genes (rs2002555 and rs11170547 in AMHR2, rs6166 in FSHR, rs10852344 &amp;lt;60kb from TNFRSF17/RUNDC2A/ GSPT1, rs12461110 in NLRP11, rs1801133 in MTHFR, rs2066470 in MTHRF, rs3810682 in BMP15, and rs615942 in COASY), and examined their association with CRA at 12-month and 24-month time points using logistic regression adjusted for age, BMI, and tamoxifen. Results: Of the 554 eligible women with SNP data and menstrual data at 12 months, 70% reported CRA; of the 458 eligible women with SNP data and menstrual data at 24 months, 69% reported CRA. The two SNPs in AMHR2 showed suggestive associations with CRA at 12 and 24 months. [Final results pending]. Conclusions: Genetic variation in AMHR2 may be associated with CRA. Additional research will be needed to validate these findings in other breast cancer survivors and to identify additional SNPs that may be associated with CRA. Together with other clinical factors, genetic variation may improve our ability to predict who will experience CRA, and may inform reproductive and treatment decision-making in cancer patients. Citation Format: Ruddy KJ, Rack B, Schwitulla J, Lambrechts D, Haeberle L, Schramm A, Trapp E, Scholz C, Beutler AS, Ginsburg E, Couch F, Partridge AH, Wang L, Weinshilboum RM, Janni W, Vachon C, Fasching P. Genetic predictors of chemotherapy-related amenorrhea. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-10-07.

Decision Making about Contralateral Prophylactic Mastectomy Among BRCA1/2 Noncarriers with Newly-diagnosed Breast Cancer: Examining Cognitive, Emotional, and Sociodemographic Influences

Abstract Pre-surgical BRCA1/2 genetic testing provides valuable risk information to guide a newly-diagnosed breast cancer patient's decision about whether to have a contralateral prophylactic mastectomy (CPM) to reduce her future risk of cancer in her unaffected breast. Although BRCA1/2 mutation noncarriers face a much lower objective ten-year risk of developing contralateral disease (approximately 3–10%) as compared to the risk of BRCA1/2 mutation carriers (27–37%), some noncarriers still choose to undergo a CPM. The psychosocial factors that motivate this decision are not well understood and warrant investigation. Thus, as part of a prospective study of pre-surgical BRCA1/2 testing, we examined the frequency and psychosocial correlates of the decision to undergo a CPM among newly-diagnosed breast cancer patients who were identified as BRCA1/2 mutation noncarriers. Self-report questionnaire data from 90 BRCA1/2 noncarriers (median age = 43 years, range = 29–59) were analyzed. A sizeable minority of the BRCA1/2 noncarriers (24.4%) chose to undergo a CPM after learning their mutation status (compared to 88% of the 8 BRCA1/2 carriers in the sample). Both bivariate and multivariable analyses indicated that perceiving that one's physician had recommended CPM (OR = 11.17, P = 0.007), perceiving greater risk for contralateral breast cancer (OR = 6.46, P = 0.02), and perceiving greater pros of CPM (OR = 1.37, P = 0.004) were all significantly associated with noncarriers' decision to undergo CPM. However, factors including age, Ashkenazi Jewish ethnicity, breast cancer-related distress, perceived cons of CPM, and decisional conflict regarding CPM were not related to the CPM decision (all ps &amp;gt; 0.05). Results demonstrate that although noncarriers' decision making regarding CPM was unrelated to sociodemographic and emotional factors, their cognitive perceptions of contralateral disease risk, surgical benefits, and physician recommendations were particularly important. Future studies should examine the content of patient-physician communication regarding CPM and hereditary risk in greater detail, and explore how these conversations shape and interact with women's past experiences, emotions, and beliefs to influence their cancer prevention decisions.

A systematic review of factors influencing older adults' decision to accept or decline cancer treatment.

Cancer is a disease that affects mostly older adults. Older adults often have other chronic health conditions in addition to cancer and may have different health priorities, both of which can impact cancer treatment decision-making. However, no systematic review of factors that influence an older cancer patient's decision to accept or decline cancer treatment has been conducted. Systematic review of the literature published between inception of the databases and February 2013. Dutch, English, French or German articles reporting on qualitative studies, cross-sectional, longitudinal observational or intervention studies describing factors why older adults accepted or declined cancer treatment examining actual treatment decisions were included. Ten databases were used. Two independent reviewers reviewed manuscripts and performed data abstraction using a standardized form and the quality of studies was assessed with the Mixed Methods Appraisal Tool. Of 17,343 abstracts reviewed, a total of 38 studies were included. The majority focused on breast and prostate cancer treatment decisions and most studies used a qualitative design. Important factors for accepting treatment were convenience and success rate of treatment, seeing necessity of treatment, trust in the physician and following the physician's recommendation. Factors important for declining cancer treatment included concerns about the discomfort of the treatments, fear of side effects and transportation difficulties. Although the reasons why older adults with cancer accepted or declined treatment varied considerably, the most consistent determinant was physician recommendation. Further studies using large, representative samples and exploring decision-making incorporating health literacy and comorbidity are needed.

Factors that may influence the willingness of cancer patients to consent for biobanking.

Broad or general consent given by cancer patients for their tissue, blood, and clinical information to be stored in institutional biorepositories is fundamental to enable future ethical translational cancer research. The decision to consent for biobanking will contribute to the development of advanced diagnostic and prognostic tests, as well as new therapies to improve patient outcomes. While the rate of patient participation in biobanking programs is generally reported as high worldwide, few studies have investigated factors that may influence this decision. Biobanking at our medical research institute, an associated public (government-run) university hospital, and private hospital has been established for over 20 years, with collection of certain tumor types embedded in the research culture of these institutions. In this study, we investigated factors that may influence a cancer patient's decision to give broad consent for biobanking of their specimens. Data on patient consent were collected over a 6-month period from both government and private hospitals associated with our medical research institute. Factors considered included gender, patient age at surgery, type of malignancy (breast, duodenal, cervical, endometrial, gastric, liver, esophageal, ovarian, pancreatic, pelvic, uterine, or vulval), type of institution where surgery was performed, and timing of consent. Of 171 cancer patients, 159 (93%) gave broad consent for biobanking of their tissue and blood specimens for future cancer research projects receiving ethical and scientific approval. None of the factors analyzed was shown to influence a patient's decision to contribute biological specimens and clinical data to a biorepository for future medical research. Biobanking for future ethically and scientifically approved research projects in an established institution is an initiative that receives strong support from patients undergoing cancer surgery, independent of factors including gender, age, type of tumor, type of institution where surgery was performed, or timing of consent.

1433P - Factors Associatd with Surrogate Decision-Making in Advanced Cancer Patients:a Longitudinal Study

ABSTRACT Purpose Although surrogate decision-making in cancer patients is well-known, few studies investigating the prevalence of surrogate decision-making over time have been reported. The objectives of this study were to investigate the level of surrogate decision-making in advanced cancer patients over time and the impact of demographic and clinical variables on surrogate decision-making. Methods The level of surrogate decision-making was measured in 572 consecutive cancer patients who died between January 1 and December 31, 2009. We reviewed 8,639 informed consent forms of these patients, calculated the proportion of decisions made by a surrogate (PDS) for each patient, and analyzed the association of PDS with demographic and clinical variables. Results Surrogates completed 40.3% of all consent forms. The prevalence of surrogate decision-making was higher in the end-of-life period (death 365 days). Surrogates signed consent forms more frequently for do-not-resuscitate directives, intensive care unit admission, emergency hemodialysis, surgery and invasive interventions compared with chemotherapy, radiotherapy, and diagnostic tests (OR = 3.88, P Conclusions Surrogate decision-making was frequently observed among Korean cancer patients in this study, especially when the patient's death was imminent, and for decisions related to end-of-life care. Surrogates were also frequently involved in decisions for elderly or rapidly deteriorating patients. Healthcare professionals should consider the significant role of familial surrogates in the end-of-life period; comprehensive approaches are needed to preserve the best interest of the patients. Disclosure All authors have declared no conflicts of interest.

Surrogate decision-making in Korean patients with advanced cancer: a longitudinal study

Although surrogate decision-making in cancer patients is well-known, few studies investigating the prevalence of surrogate decision-making over time have been reported. The objectives of this study were to investigate the level of surrogate decision-making in advanced cancer patients over time and the impact of demographic and clinical variables on surrogate decision-making. The level of surrogate decision-making was measured in 572 consecutive cancer patients who died between January 1 and December 31, 2009. We reviewed 8,639 informed consent forms of these patients, calculated the proportion of decisions made by a surrogate (PDS) for each patient, and analyzed the association of PDS with demographic and clinical variables. Surrogates completed 40.3 % of all consent forms. The prevalence of surrogate decision-making was higher in the end-of-life period (death <7 days, OR = 29.05; reference, >365 days). Surrogates signed consent forms more frequently for do-not-resuscitate directives, intensive care unit admission, emergency hemodialysis, surgery and invasive interventions compared with chemotherapy, radiotherapy, and diagnostic tests (OR = 3.88, P < 0.001). Patients of older age (P = 0.036) and those with a shorter duration of management (P < 0.001) were independently associated with greater PDS. Surrogate decision-making was frequently observed among Korean cancer patients in this study, especially when the patient's death was imminent, and for decisions related to end-of-life care. Surrogates were also frequently involved in decisions for elderly or rapidly deteriorating patients. Healthcare professionals should consider the significant role of familial surrogates in the end-of-life period; comprehensive approaches are needed to preserve the best interest of the patients.

Why Cancer Patients Enter Randomized Clinical Trials: Exploring the Factors That Influence Their Decision

Few interventions have been designed and tested to improve recruitment to clinical trials in oncology. The multiple factors influencing patients' decisions have made the prioritization of specific interventions challenging. The present study was undertaken to identify the independent predictors of a cancer patient's decision to enter a randomized clinical trial. A list of factors from the medical literature was augmented with a series of focus groups involving cancer patients, physicians, and clinical research associates (CRAs). A series of questionnaires was developed with items based on these factors and were administered concurrently to 189 cancer patients, their physicians, and CRAs following the patient's decision regarding trial entry. Forward logistic regression modeling was performed using the items significantly correlated (by univariate analysis) with the decision to enter a clinical trial. A number of items were significantly correlated with the patient's decision. In the multivariate logistic regression model, the patient's perception of personal benefit was the most important, with an odds ratio (OR) of 3.08 (P < .05). CRA-related items involving supportive aspects of the decision-making process were also important. These included whether the CRA helped with the decision (OR = 1.71; P < .05), and whether the decision was hard for the patient to make (OR = 0.52; P < .05). Strategies that better address the potential benefits of trial entry may result in improved accrual. Interventions or aids that focus on the supportive aspects of the decision-making process while respecting the need for information and patient autonomy may also lead to meaningful improvements in accrual.

Social and psychological aspects of cancer patient's decision making in Russian clinical practice

Social and psychological aspects of cancer patient's decision making in Russian clinical practice