Citations

Abstract Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer’s disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer’s disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset −9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer’s disease, which is alike sporadic Alzheimer’s disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer’s disease.

The NCCN Guidelines for Rectal Cancer provide recommendations for the diagnosis, evaluation, treatment, and follow-up of patients with rectal cancer. These NCCN Guidelines Insights summarize the panel discussion behind recent important updates to the guidelines. These updates include clarifying the definition of rectum and differentiating the rectum from the sigmoid colon; the total neoadjuvant therapy approach for localized rectal cancer; and biomarker-targeted therapy for metastatic colorectal cancer, with a focus on new treatment options for patients with BRAF V600E– or HER2 amplification–positive disease.

Treatment is complex for patients with head and neck (H&N) cancers with specific site of disease, stage, and pathologic findings guiding treatment decision-making. Treatment planning for H&N cancers involves a multidisciplinary team of experts. This article describes supportive care recommendations in the NCCN Guidelines for Head and Neck Cancers, as well as the rationale supporting a new section on imaging recommendations for patients with H&N cancers. This article also describes updates to treatment recommendations for patients with very advanced H&N cancers and salivary gland tumors, specifically systemic therapy recommendations.

Abstract Background: A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening. Methods: United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3–T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups. Results: The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age. Conclusions: PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS. Impact: Personalized genetic risk assessments could inform prostate cancer screening decisions.

The NCCN Guidelines for Cervical Cancer provide recommendations for diagnostic workup, staging, and treatment of patients with the disease. These NCCN Guidelines Insights focus on recent updates to the guidelines, including changes to first- and second-line systemic therapy recommendations for patients with recurrent or metastatic disease, and emerging evidence on a new histopathologic classification system for HPV-related endocervical adenocarcinoma.

Background Clinical practice guidelines (CPGs) are evidence‐based guidelines that serve as a standard of care in oncology practice, reimbursements, and quality improvement initiatives. To our knowledge, the extent of financial conflicts of interest (FCOIs) in National Comprehensive Cancer Network (NCCN) guidelines have not been systemically evaluated. The current study evaluated the extent of FCOIs in the NCCN CPGs for the most common malignancies in the United States. Methods The authors examined the latest 2019 versions of the NCCN CPGs for the 10 most common cancers by incidence in the United States. Using disclosure lists, they catalogued the FCOIs for the panelists under various categories outlined in the CPG. The authors also tabulated the companies and institutions involved in each panel disclosure. An “episode” describes 1 instance of participation of a panelist in 1 company in 1 category of each guideline. “Affiliation” describes an industrial, commercial, or institutional affiliation reported by a panelist in each episode. Results Of the 491 panelists on the CPG panel, 483 (98.3%) completed FCOI disclosures. A total of 224 (46.4%) reported at least 1 FCOI episode. A total of 1103 episodes were disclosed with an average of 4.9 episodes reported per panelist with FCOIs. Acting as part of scientific advisory boards, as a consultant, or as an expert witness was the most common FCOI category (19.9%). A total of 191 companies were associated with 1103 episodes of FCOI. The top companies were Bristol‐Myers Squibb, Merck, Genentech, and AstraZeneca. Among cancers, the prevalence of FCOIs was highest for lung cancer (56%), bladder cancer (52%), pancreatic cancer (52%), non‐Hodgkin lymphoma (50%), kidney cancer (49%), colorectal cancer (43%), breast cancer (42%), melanoma (40%), prostate cancer (38%), and uterine cancer (32%). Among the panelists with FCOIs, 26%, 17%, and 57%, respectively, reported 1, 2, and >3 episodes. There were 127 episodes noted among the CPG chairs and/or vice chairs who reported FCOIs (mean, 6.4 episodes). The chairs and/or vice chairs of CPGs for uterine cancer, pancreatic cancer, melanoma, and prostate cancer were not found to have any FCOIs. Conclusions FCOIs are very prevalent among NCCN CPG panelists. In nearly one‐half of the CPGs, the majority of the panelists had at least 1 FCOI. Greater than one‐half of the CPG chairs and/or vice chairs reported multiple FCOIs. Further research studies are necessary to determine the impact of these FCOIs.

OBJECTIVE Limited information is available about glycemic outcomes with a closed-loop control (CLC) system compared with a predictive low-glucose suspend (PLGS) system. RESEARCH DESIGN AND METHODS After 6 months of use of a CLC system in a randomized trial, 109 participants with type 1 diabetes (age range, 14–72 years; mean HbA1c, 7.1% [54 mmol/mol]) were randomly assigned to CLC (N = 54, Control-IQ) or PLGS (N = 55, Basal-IQ) groups for 3 months. The primary outcome was continuous glucose monitor (CGM)-measured time in range (TIR) for 70–180 mg/dL. Baseline CGM metrics were computed from the last 3 months of the preceding study. RESULTS All 109 participants completed the study. Mean ± SD TIR was 71.1 ± 11.2% at baseline and 67.6 ± 12.6% using intention-to-treat analysis (69.1 ± 12.2% using per-protocol analysis excluding periods of study-wide suspension of device use) over 13 weeks on CLC vs. 70.0 ± 13.6% and 60.4 ± 17.1% on PLGS (difference = 5.9%; 95% CI 3.6%, 8.3%; P < 0.001). Time >180 mg/dL was lower in the CLC group than PLGS group (difference = −6.0%; 95% CI −8.4%, −3.7%; P < 0.001) while time <54 mg/dL was similar (0.04%; 95% CI −0.05%, 0.13%; P = 0.41). HbA1c after 13 weeks was lower on CLC than PLGS (7.2% [55 mmol/mol] vs. 7.5% [56 mmol/mol], difference −0.34% [−3.7 mmol/mol]; 95% CI −0.57% [−6.2 mmol/mol], −0.11% [1.2 mmol/mol]; P = 0.0035). CONCLUSIONS Following 6 months of CLC, switching to PLGS reduced TIR and increased HbA1c toward their pre-CLC values, while hypoglycemia remained similarly reduced with both CLC and PLGS.

e13681 Background: Cell-free tumor DNA or circulating tumor DNA tests are increasingly used in clinical care to detect somatic mutations from solid tumors. However, data on laboratory performance characteristics using standardized samples is limited. Methods: Well-characterized reference materials were used for the College of American Pathologists (CAP) cell-free tumor DNA proficiency testing surveys, which consisted of stabilized DNA fragmented to simulate cell-free DNA in a synthetic plasma matrix. For the 2018A, 2018B, 2019A and 2019B surveys, laboratories tested for hotspot mutations (single and dinucleotide sequence changes) in EGFR, BRAF, KRAS, NRAS, and IDH1 at variant allele fractions ranging from 0.1% - 1.0%. As per CAP proficiency testing standards, results were scored according to the known mutation(s) engineered at designated variant allele fractions in each PT sample. Nine laboratories were excluded from analysis because they provided incomplete results. Statistical significance was calculated using a multivariate logistic regression model. Results: In 2018 and 2019, 101 laboratories submitted survey results for at least one proficiency testing mailing. There were 5088 total proficiency testing responses for EGFR, BRAF, KRAS, NRAS, and IDH1 mutations across 12 different samples. For the 3585 responses submitted for BRAF, KRAS, NRAS, and IDH1, sensitivity ranged from 94.6 – 100%, while specificity exceeded 99%. There were no significant differences in performance between analytical methodologies for BRAF, KRAS, NRAS, and IDH1 mutations. Performance characteristics for EGFR mutations among the 1503 responses showed a combined sensitivity of 87.1% and specificity of 98.7%. For laboratories detecting mutations in EGFR, next-generation sequencing methods exhibited a sensitivity (true positivity) of 95.7% while the sensitivity of non-NGS methods was lower at 81.7% ( P= 0.02). Conclusions: These findings demonstrate high sensitivity and specificity for clinical laboratories performing cell-free tumor DNA tests. For EGFR mutations, NGS outperformed non-NGS methods. These data suggest excellent overall agreement among laboratories performing clinical cell-free tumor DNA tests. Further investigation across variant allele fractions and additional variant types is warranted.