Methylthioadenosine Phosphorylase Genomic Loss in Advanced Gastrointestinal Cancers.

BACKGROUND: One of the most common sporadic homozygous deletions in cancers is 9p21 loss, which includes the genes methylthioadenosine phosphorylase (MTAP), CDKN2A, and CDKN2B, and has been correlated with worsened outcomes and immunotherapy resistance. MTAP-loss is a developing drug target through synthetic lethality with MAT2A and PMRT5 inhibitors. The purpose of this study is to investigate the prevalence and genomic landscape of MTAP-loss in advanced gastrointestinal (GI) tumors and investigate its role as a prognostic biomarker. MATERIALS AND METHODS: We performed next-generation sequencing and comparative genomic and clinical analysis on an extensive cohort of 64 860 tumors comprising 5 GI cancers. We compared the clinical outcomes of patients with GI cancer harboring MTAP-loss and MTAP-intact tumors in a retrospective study. RESULTS: The prevalence of MTAP-loss in GI cancers is 8.30%. MTAP-loss was most prevalent in pancreatic ductal adenocarcinoma (PDAC) at 21.7% and least in colorectal carcinoma (CRC) at 1.1%. MTAP-loss tumors were more prevalent in East Asian patients with PDAC (4.4% vs 3.2%, P = .005) or intrahepatic cholangiocarcinoma (IHCC; 6.4% vs 4.3%, P = .036). Significant differences in the prevalence of potentially targetable genomic alterations (ATM, BRAF, BRCA2, ERBB2, IDH1, PIK3CA, and PTEN) were observed in MTAP-loss tumors and varied according to tumor type. MTAP-loss PDAC, IHCC, and CRC had a lower prevalence of microsatellite instability or elevated tumor mutational burden. Positive PD-L1 tumor cell expression was less frequent among MTAP-loss versus MTAP-intact IHCC tumors (23.2% vs 31.2%, P = .017). CONCLUSION: In GI cancers, MTAP-loss occurs as part of 9p21 loss and has an overall prevalence of 8%. MTAP-loss occurs in 22% of PDAC, 15% of IHCC, 8.7% of gastroesophageal adenocarcinoma, 2.4% of hepatocellular carcinoma, and 1.1% of CRC and is not mutually exclusive with other targetable mutations.

Prevalence of targetable genomic alterations in young women with advanced breast cancer: a cross-sectional study.

PURPOSE: Approximately 5% of breast cancers each year are diagnosed in young women < 40 years who tend to have worse clinical outcomes. We compared genomic alterations using comprehensive genomic profiling (CGP) of tumor tissue among very young women (< 30 years) and young women (30-39 years) compared to women ≥ 40 years at diagnosis. METHODS: 2049 advanced breast cancer cases were submitted to Foundation Medicine within a 22-month window for CGP. Hybrid-capture based CGP was performed to evaluate all classes of genomic alterations. Tumor mutational burden was determined on at least 0.8 Mbp of sequenced DNA and microsatellite instability was determined on at least 95 loci. Immunocyte PD-L1 expression was determined by immunohistochemistry. RESULTS: Of the total cases, 28 (1.37%) were < 30 years, 159 (7.76%) were 30-39 years, and 1862 (90.87%) were ≥ 40 at time of diagnosis. Breast tumors were less likely to be estrogen receptor positive in younger women (54% of < 30 years, p > 0.05; 60% of 30-39 years, p < 0.001; 69.4% of ≥ 40 years) and more likely to be triple negative (43%, p = 0.05; 33%, p = 0.05; 26.1% respectively). Young women had higher rates of BRCA1 mutations (17.9% <30 years, p < 0.001; 10.1% 30-39 years, p < 0.001; 2.6% ≥40 years), but lower rates of CDH1 (7.1% <30 years, p > 0.05; 5.0% 30-39 years, p < 0.001; 15.4% ≥40 years) and PIK3CA mutations (17.9% <30 years, p = 0.02; 17.6% 30-39 years, p < 0.001; 40.0% ≥40 years). CONCLUSION: Our findings contribute to the growing literature demonstrating unique genetic profiles among young women diagnosed with breast cancer, compared to older women.

Comprehensive genomic profiling of ESR1, PIK3CA, AKT1, and PTEN in HR(+)HER2(-) metastatic breast cancer: prevalence along treatment course and predictive value for endocrine therapy resistance in real-world practice.

BACKGROUND: The treatment landscape for HR(+)HER2(-) metastatic breast cancer (MBC) is evolving for patients with ESR1 mutations (mut) and PI3K/AKT pathway genomic alterations (GA). We sought to inform clinical utility for comprehensive genomic profiling (CGP) using tissue (TBx) and liquid biopsies (LBx) in HR(+)HER2(-) MBC. METHODS: Records from a de-identified breast cancer clinicogenomic database for patients who underwent TBx/LBx testing at Foundation Medicine during routine clinical care at ~ 280 US cancer clinics between 01/2011 and 09/2023 were assessed. GA prevalence [ESR1mut, PIK3CAmut, AKT1mut, PTENmut, and PTEN homozygous copy loss (PTENloss)] were calculated in TBx and LBx [stratified by ctDNA tumor fraction (TF)] during the first three lines of therapy. Real-world progression-free survival (rwPFS) and overall survival (rwOS) were compared between groups by Cox models adjusted for prognostic factors. RESULTS: ~ 60% of cases harbored 1 + GA in 1st-line TBx (1266/2154) or LBx TF ≥ 1% (80/126) and 26.5% (43/162) in LBx TF < 1%. ESR1mut was found in 8.1% TBx, 17.5% LBx TF ≥ 1%, and 4.9% LBx TF < 1% in 1st line, increasing to 59% in 3rd line (LBx TF ≥ 1%). PTENloss was detected at higher rates in TBx (4.3%) than LBx (1% in TF ≥ 1%). Patients receiving 1st-line aromatase inhibitor + CDK4/6 inhibitor (n = 573) with ESR1mut had less favorable rwPFS and rwOS versus ESR1 wild-type; no differences were observed for fulvestrant + CDK4/6 inhibitor (n = 348). CONCLUSION: Our study suggests obtaining TBx for CGP at time of de novo/recurrent diagnosis, followed by LBx for detecting acquired GA in 2nd + lines. Reflex TBx should be considered when ctDNA TF < 1%.

Variable Genomic Landscapes of Advanced Melanomas with Heavy Pigmentation.

BACKGROUND: In the current study, we examined the real-world prevalence of highly pigmented advanced melanomas (HPMel) and the clinicopathologic, genomic, and ICPI biomarker signatures of this class of tumors. MATERIALS AND METHODS: Our case archive of clinical melanoma samples for which the ordering physician requested testing for both PD-L1 immunohistochemistry (IHC) and comprehensive genomic profiling (CGP) was screened for HPMel cases, as well as for non-pigmented or lightly pigmented advanced melanoma cases (LPMel). RESULTS: Of the 1268 consecutive melanoma biopsies in our archive that had been submitted for PD-L1 IHC, 13.0% (165/1268) were HPMel and 87.0% (1103/1268) were LPMel. In the HPMel cohort, we saw a significantly lower tumor mutational burden (TMB, median 8.8 mutations/Mb) than in the LPMel group (11.4 mut/Mb), although there was substantial overlap. In examining characteristic secondary genomic alterations (GA), we found that the frequencies of GA in TERTp, CDKN2A, TP53, and PTEN were significantly lower in the HPMel cases than in LPMel. A higher rate of GA in CTNNB1, APC, PRKAR1A, and KIT was identified in the HPMel cohort compared with LPMel. CONCLUSIONS: In this study, we quantified the failure rates of melanoma samples for PD-L1 testing due to high melanin pigmentation and showed that CGP can be used in these patients to identify biomarkers that can guide treatment decisions for HPMel patients. Using this practical clinical definition for tumor pigmentation, our results indicate that HPMel are frequent at 13% of melanoma samples, and in general appear molecularly less developed, with a lower TMB and less frequent secondary GA of melanoma progression.

Association of CD274 (PD-L1) Copy Number Changes with Immune Checkpoint Inhibitor Clinical Benefit in Non-Squamous Non-Small Cell Lung Cancer.

BACKGROUND: We sought to characterize response to immune checkpoint inhibitor (ICI) in non-squamous non-small cell lung cancer (NSCLC) across various CD274 copy number gain and loss thresholds and identify an optimal cutoff. MATERIALS AND METHODS: A de-identified nationwide (US) real-world clinico-genomic database was leveraged to study 621 non-squamous NSCLC patients treated with ICI. All patients received second-line ICI monotherapy and underwent comprehensive genomic profiling as part of routine clinical care. Overall survival (OS) from start of ICI, for CD274 copy number gain and loss cohorts across varying copy number thresholds, were assessed. RESULTS: Among the 621 patients, patients with a CD274 CN greater than or equal to specimen ploidy +2 (N = 29) had a significantly higher median (m) OS when compared with the rest of the cohort (N = 592; 16.1 [8.9-37.3] vs 8.6 [7.1-10.9] months, hazard ratio (HR) = 0.6 [0.4-1.0], P-value = .05). Patients with a CD274 copy number less than specimen ploidy (N = 299) trended toward a lower mOS when compared to the rest of the cohort (N = 322; 7.5 [5.9-11.3] vs 9.6 [7.9-12.8] months, HR = 0.9 [0.7-1.1], P-value = .3). CONCLUSION: This work shows that CD274 copy number gains at varying thresholds predict different response to ICI blockade in non-squamous NSCLC. Considering these data, prospective clinical trials should further validate these findings, specifically in the context of PD-L1 IHC test results.

Black Women Are Less Likely to Be Classified as High-Risk for Breast Cancer Using the Tyrer-Cuzick 8 Model.

BACKGROUND: Breast cancer risk assessment is a powerful tool that guides recommendations for supplemental breast cancer screening and genetic counseling. The Tyrer-Cuzick 8 (TC8) model is widely used for calculating breast cancer risk and thus helps determine if women qualify for supplemental screening or genetic counseling. However, the TC8 model may underestimate breast cancer risk in Black women. This study sought to assess this disparity. METHODS: Data on race, breast density, body mass index (BMI), and TC8 scores were retrospectively extracted from the electronic medical record (EMR). Logistic regressions were run to evaluate racial differences in TC8 scores. Summary and correlation statistics determined relationships between BMI, breast density, and race. Rank biserial correlations were employed to explore the impact of breast density and BMI on TC8 scores. RESULTS: Of 15,356 patients, 5796 were White and 5813 were Black. Black patients had higher rates of BMI ≥ 27 compared with White women (79.2% vs. 45.7%), lower rates of breast density (35.1% vs. 56.2%), and lower rates of high-risk TC8 scores (10.7% vs. 17.5%, OR = 1.6646). There was an inverse relationship between TC8 score and BMI (rrb = - 0.04) and a direct relationship between TC8 score and breast density (rrb = 0.37). DISCUSSION: Black women are less likely to have high-risk TC8 scores despite having only marginally lower breast cancer incidence rates and higher breast cancer mortality rates than White women. This suggests that the TC8 model underestimates breast cancer risk in Black women, possibly due to lower rates of breast density and higher BMIs among Black women.

Correction: Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Qualitative study of system-level factors related to genomic implementation.

PURPOSE: Research on genomic medicine integration has focused on applications at the individual level, with less attention paid to implementation within clinical settings. Therefore, we conducted a qualitative study using the Consolidated Framework for Implementation Research (CFIR) to identify system-level factors that played a role in implementation of genomic medicine within Implementing GeNomics In PracTicE (IGNITE) Network projects. METHODS: Up to four study personnel, including principal investigators and study coordinators from each of six IGNITE projects, were interviewed using a semistructured interview guide that asked interviewees to describe study site(s), progress at each site, and factors facilitating or impeding project implementation. Interviews were coded following CFIR inner-setting constructs. RESULTS: Key barriers included (1) limitations in integrating genomic data and clinical decision support tools into electronic health records, (2) physician reluctance toward genomic research participation and clinical implementation due to a limited evidence base, (3) inadequate reimbursement for genomic medicine, (4) communication among and between investigators and clinicians, and (5) lack of clinical and leadership engagement. CONCLUSION: Implementation of genomic medicine is hindered by several system-level barriers to both research and practice. Addressing these barriers may serve as important facilitators for studying and implementing genomics in practice.

Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

PurposeImplementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing Genomics in Practice (IGNITE) Network's efforts to promote (i) a broader understanding of genomic medicine implementation research and (ii) the sharing of knowledge generated in the network.MethodsTo facilitate this goal, the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide its approach to identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross-network analyses.ResultsCMG identified 10 high-priority CFIR constructs as important for genomic medicine. Of those, eight did not have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.ConclusionWe developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

Internet-Based Assessment of Oncology Health Care Professional Learning Style and Optimization of Materials for Web-Based Learning: Controlled Trial With Concealed Allocation.

BACKGROUND: Precision medicine has resulted in increasing complexity in the treatment of cancer. Web-based educational materials can help address the needs of oncology health care professionals seeking to understand up-to-date treatment strategies. OBJECTIVE: This study aimed to assess learning styles of oncology health care professionals and to determine whether learning style-tailored educational materials lead to enhanced learning. METHODS: In all, 21,465 oncology health care professionals were invited by email to participate in the fully automated, parallel group study. Enrollment and follow-up occurred between July 13 and September 7, 2015. Self-enrolled participants took a learning style survey and were assigned to the intervention or control arm using concealed alternating allocation. Participants in the intervention group viewed educational materials consistent with their preferences for learning (reading, listening, and/or watching); participants in the control group viewed educational materials typical of the My Cancer Genome website. Educational materials covered the topic of treatment of metastatic estrogen receptor-positive (ER+) breast cancer using cyclin-dependent kinases 4/6 (CDK4/6) inhibitors. Participant knowledge was assessed immediately before (pretest), immediately after (posttest), and 2 weeks after (follow-up test) review of the educational materials. Study statisticians were blinded to group assignment. RESULTS: A total of 751 participants enrolled in the study. Of these, 367 (48.9%) were allocated to the intervention arm and 384 (51.1%) were allocated to the control arm. Of those allocated to the intervention arm, 256 (69.8%) completed all assessments. Of those allocated to the control arm, 296 (77.1%) completed all assessments. An additional 12 participants were deemed ineligible and one withdrew. Of the 552 participants, 438 (79.3%) self-identified as multimodal learners. The intervention arm showed greater improvement in posttest score compared to the control group (0.4 points or 4.0% more improvement on average; P=.004) and a higher follow-up test score than the control group (0.3 points or 3.3% more improvement on average; P=.02). CONCLUSIONS: Although the study demonstrated more learning with learning style-tailored educational materials, the magnitude of increased learning and the largely multimodal learning styles preferred by the study participants lead us to conclude that future content-creation efforts should focus on multimodal educational materials rather than learning style-tailored content.

Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data.

OBJECTIVE: Wide-scale adoption of electronic medical records (EMRs) has created an unprecedented opportunity for the implementation of Rapid Learning Systems (RLSs) that leverage primary clinical data for real-time decision support. In cancer, where large variations among patient features leave gaps in traditional forms of medical evidence, the potential impact of a RLS is particularly promising. We developed the Melanoma Rapid Learning Utility (MRLU), a component of the RLS, providing an analytical engine and user interface that enables physicians to gain clinical insights by rapidly identifying and analyzing cohorts of patients similar to their own. MATERIALS AND METHODS: A new approach for clinical decision support in Melanoma was developed and implemented, in which patient-centered cohorts are generated from practice-based evidence and used to power on-the-fly stratified survival analyses. A database to underlie the system was generated from clinical, pharmaceutical, and molecular data from 237 patients with metastatic melanoma from two academic medical centers. The system was assessed in two ways: (1) ability to rediscover known knowledge and (2) potential clinical utility and usability through a user study of 13 practicing oncologists. RESULTS: The MRLU enables physician-driven cohort selection and stratified survival analysis. The system successfully identified several known clinical trends in melanoma, including frequency of BRAF mutations, survival rate of patients with BRAF mutant tumors in response to BRAF inhibitor therapy, and sex-based trends in prevalence and survival. Surveyed physician users expressed great interest in using such on-the-fly evidence systems in practice (mean response from relevant survey questions 4.54/5.0), and generally found the MRLU in particular to be both useful (mean score 4.2/5.0) and useable (4.42/5.0). DISCUSSION: The MRLU is an RLS analytical engine and user interface for Melanoma treatment planning that presents design principles useful in building RLSs. Further research is necessary to evaluate when and how to best use this functionality within the EMR clinical workflow for guiding clinical decision making. CONCLUSION: The MRLU is an important component in building a RLS for data driven precision medicine in Melanoma treatment that could be generalized to other clinical disorders.

Guiding Oncology Patients Through the Maze of Precision Medicine.

As the role of genomics in health care grows, patients increasingly require adequate genetic literacy to fully engage in their care. This study investigated a model for delivering consumer-friendly genetic information to improve understanding of precision medicine using health literacy and learning style principles. My Cancer Genome (MCG), a freely available cancer decision support tool, was used as a testbed. MCG content on a melanoma tumor mutation, BRAF V600E, was translated to a 6th-grade reading level, incorporating multiple learning modalities. A total of 90 patients and caregivers were recruited from a melanoma clinic at an academic medical center and randomized to 3 groups. Group A (control) received an exact copy of text from MCG. Group B was given the same content with hyperlinks to videos explaining key genetic concepts, identified and labeled by the team as knowledge pearls. Group C received the translated content with the knowledge pearls embedded. Changes in knowledge were measured through pre and post questionnaires. Group C showed the greatest improvement in knowledge. The study results demonstrate that providing information based on health literacy and learning style principles can improve patients' understanding of genetic concepts, thus increasing their likelihood of taking an active role in any decision making concerning their health.

Translating genomic information into clinical medicine: lung cancer as a paradigm.

We are currently in an era of rapidly expanding knowledge about the genetic landscape and architectural blueprints of various cancers. These discoveries have led to a new taxonomy of malignant diseases based upon clinically relevant molecular alterations in addition to histology or tissue of origin. The new molecularly based classification holds the promise of rational rather than empiric approaches for the treatment of cancer patients. However, the accelerated pace of discovery and the expanding number of targeted anti-cancer therapies present a significant challenge for healthcare practitioners to remain informed and up-to-date on how to apply cutting-edge discoveries into daily clinical practice. In this Perspective, we use lung cancer as a paradigm to discuss challenges related to translating genomic information into the clinic, and we present one approach we took at Vanderbilt-Ingram Cancer Center to address these challenges.

Characterization of breast cancers with PI3K mutations in an academic practice setting using SNaPshot profiling.

Mutations in the PIK3CA gene are common in breast cancer and represent a clinically useful therapeutic target. Several larger, population-based studies have shown a positive prognostic significance associated with these mutations. This study aims to further identify characteristics of patients harboring PIK3CA mutations while evaluating the clinical impact of genomic testing for these mutations. Tumors from 312 patients at Vanderbilt-Ingram Cancer Center were analyzed for PIK3CA mutations using a multiplex screening assay (SNaPshot). Mutation rates, receptor status, histopathologic characteristics, and time to recurrence were assessed. The number of patients participating in clinical trials, specifically trials relating to the PIK3CA mutation, was examined. Statistically significant differences between wild-type and mutated tumors were determined using the Wilcoxon, Pearson, and Fischer exact tests. The PIK3CA mutation was found in 25 % of tumors tested. Patients with PIK3CA mutations were significantly more likely to express hormone receptors, be of lower combined histological grade, and have a reduced time to recurrence. Patients found to have a PIK3CA mutation were significantly more likely to enter a PIK3CA-specific clinical trial. In addition to confirming previously established positive prognostic characteristics of tumors harboring PIK3CA mutations, this study demonstrates the feasibility and utility of mutation profiling in a clinical setting. PIK3CA mutation testing impacted treatment and resulted in more patients entering mutation-specific clinical trials.

Impact of the 2018 ACR Supplemental Screening Recommendations on MRI Eligibility in Breast Cancer Survivors.

PURPOSE: The 2018 ACR recommendations for breast cancer screening in women at higher than average risk include new recommendations for supplemental breast MRI for patients with personal histories of breast cancer (PHBCs) who carry hereditary cancer gene mutations, have dense breast tissue, or were diagnosed before 50 years of age. In comparison, prior guidelines recommended supplemental MRI only for women with PHBCs who carried hereditary cancer gene mutations. The aim of this study was to quantify the increase in the number of patients with breast cancer for whom supplemental breast MRI would now be recommended. METHODS: Data were extracted from the electronic health records of patients presenting for screening or diagnostic mammography at an urban academic medical center between July 20, 2020, and July 19, 2021. Data extracted included patient-reported PHBC, age at time of breast cancer diagnosis, and hereditary cancer gene mutation carrier status. Descriptive statistics are reported, evaluating the rate of eligibility for supplemental breast MRI in a retrospective population given the new ACR guidelines. RESULTS: Of the 2,950 patients with self-reported PHBCs who presented for breast cancer screening in the year between July 2020 and July 2021, 1,805 (61%) met the criteria for supplemental breast MRI according to the 2018 guidelines compared with only 3.6% using pre-2018 guidelines. CONCLUSIONS: Measuring the impact of the 2018 ACR supplemental MRI recommendations using real-world data at a single urban academic medical center demonstrated a 15-fold increase in potential eligibility for supplemental breast MRI in patients with PHBCs.

Identifying the status of genetic lesions in cancer clinical trial documents using machine learning.

BACKGROUND: Many cancer clinical trials now specify the particular status of a genetic lesion in a patient's tumor in the inclusion or exclusion criteria for trial enrollment. To facilitate search and identification of gene-associated clinical trials by potential participants and clinicians, it is important to develop automated methods to identify genetic information from narrative trial documents. METHODS: We developed a two-stage classification method to identify genes and genetic lesion statuses in clinical trial documents extracted from the National Cancer Institute's (NCI's) Physician Data Query (PDQ) cancer clinical trial database. The method consists of two steps: 1) to distinguish gene entities from non-gene entities such as English words; and 2) to determine whether and which genetic lesion status is associated with an identified gene entity. We developed and evaluated the performance of the method using a manually annotated data set containing 1,143 instances of the eight most frequently mentioned genes in cancer clinical trials. In addition, we applied the classifier to a real-world task of cancer trial annotation and evaluated its performance using a larger sample size (4,013 instances from 249 distinct human gene symbols detected from 250 trials). RESULTS: Our evaluation using a manually annotated data set showed that the two-stage classifier outperformed the single-stage classifier and achieved the best average accuracy of 83.7% for the eight most frequently mentioned genes when optimized feature sets were used. It also showed better generalizability when we applied the two-stage classifier trained on one set of genes to another independent gene. When a gene-neutral, two-stage classifier was applied to the real-world task of cancer trial annotation, it achieved a highest accuracy of 89.8%, demonstrating the feasibility of developing a gene-neutral classifier for this task. CONCLUSIONS: We presented a machine learning-based approach to detect gene entities and the genetic lesion statuses from clinical trial documents and demonstrated its use in cancer trial annotation. Such methods would be valuable for building information retrieval tools targeting gene-associated clinical trials.

Informatics in radiology: improving clinical work flow through an AIM database: a sample web-based lesion tracking application.

Quantitative assessments on images are crucial to clinical decision making, especially in cancer patients, in whom measurements of lesions are tracked over time. However, the potential value of quantitative approaches to imaging is impeded by the difficulty and time-intensive nature of compiling this information from prior studies and reporting corresponding information on current studies. The authors believe that the quantitative imaging work flow can be automated by making temporal data computationally accessible. In this article, they demonstrate the utility of the Annotation and Image Markup standard in a World Wide Web-based application that was developed to automatically summarize prior and current quantitative imaging measurements. The system calculates the Response Evaluation Criteria in Solid Tumors metric, along with several alternative indicators of cancer treatment response, by using the data stored in the annotation files. The application also allows the user to overlay the recorded metrics on the original images for visual inspection. Clinical evaluation of the system demonstrates its potential utility in accelerating the standard radiology work flow and in providing a means to evaluate alternative response metrics that are difficult to compute by hand. The system, which illustrates the utility of capturing quantitative information in a standard format and linking it to the image from which it was derived, could enhance quantitative imaging in clinical practice without adversely affecting the current work flow.

Preferences in Oncology History Documentation Styles Among Clinical Practitioners.

PURPOSE: Clinical notes function as the de facto handoff between providers and assume great importance during unplanned medical encounters. An organized and thorough oncology history is essential in care coordination. We sought to understand reader preferences for oncology history organization by comparing between chronologic and narrative formats. METHODS: A convenience sample of 562 clinicians from 19 National Comprehensive Cancer Network Member Institutions responded to a survey comparing two formats of oncology histories, narrative and chronologic, for the same patient. Both histories were consensus-derived real-world examples. Each history was evaluated using semantic differential attributes (thorough, useful, organized, comprehensible, and succinct). Respondents choose a preference between the two styles for history gathering and as the basis of a new note. Open-ended responses were also solicited. RESULTS: Respondents preferred the chronologic over the narrative history to prepare for a visit with an unknown patient (66% preference) and as a basis for their own note preparation (77% preference) (P < .01). The chronologic summary was preferred in four of the five measured attributes (useful, organized, comprehensible, and succinct); the narrative summary was favored for thoroughness (P < .01). Open-ended responses reflected the attribute scoring and noted the utility of content describing social determinants of health in the narrative history. CONCLUSION: Respondents of this convenience sample preferred a chronologic oncology history to a concise narrative history. Further studies are needed to determine the optimal structure and content of chronologic documentation for oncology patients and the provider effort to use this format.