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PURPOSE: Merkel cell carcinoma (MCC) is an aggressive skin cancer with a 40% recurrence rate, lacking effective prognostic biomarkers and surveillance methods. This prospective, multicenter, observational study aimed to evaluate circulating tumor DNA (ctDNA) as a biomarker for detecting MCC recurrence. METHODS: Plasma samples, clinical data, and imaging results were collected from 319 patients. A tumor-informed ctDNA assay was used for analysis. Patients were divided into discovery (167 patients) and validation (152 patients) cohorts. Diagnostic performance, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), was assessed. RESULTS: ctDNA showed high sensitivity, 95% (discovery; 95% CI, 87 to 99) and 94% (validation; 95% CI, 85 to 98), for detecting disease at enrollment, with corresponding specificities of 90% (95% CI, 82 to 95) and 86% (95% CI, 77 to 93). A positive ctDNA during surveillance indicated increased recurrence risk, with hazard ratios (HRs) of 6.8 (discovery; 95% CI, 2.9 to 16) and 20 (validation; 95% CI, 8.3 to 50). The PPV for clinical recurrence at 1 year after a positive ctDNA test was 69% (discovery; 95% CI, 32 to 91) and 94% (validation; 95% CI, 71 to 100), respectively. The NPV at 135 days after a negative ctDNA test was 94% (discovery; 95% CI, 90 to 97) and 93% (validation; 95% CI, 89 to 97), respectively. Patients positive for ctDNA within 4 months after treatment had higher rates of recurrence, with 1-year rates of 74% versus 21% (adjusted HR, 7.4 [95% CI, 2.7 to 20]). CONCLUSION: ctDNA testing exhibited high prognostic accuracy in detecting MCC recurrence, suggesting its potential to reduce frequent surveillance imaging. ctDNA also identifies high-risk patients who need more frequent imaging and may be best suited for adjuvant therapy trials.

INTRODUCTION: The primary objective of this study was to determine whether workplace culture in academic oncology differed by gender, during the COVID-19 pandemic. MATERIALS AND METHODS: We used the Culture Conducive to Womens Academic Success (CCWAS), a validated survey tool, to investigate the academic climate at an NCI-designated Cancer Center. We adapted the CCWAS to be applicable to people of all genders. The full membership of the Cancer Center was surveyed (total faculty = 429). The questions in each of 4 CCWAS domains (equal access to opportunities, work-life balance, freedom from gender bias, and leadership support) were scored using a 5-point Likert scale. Median score and interquartile ranges for each domain were calculated. RESULTS: A total of 168 respondents (men = 58, women = 106, n = 4 not disclosed) submitted survey responses. The response rate was 39% overall and 70% among women faculty. We found significant differences in perceptions of workplace culture by gender, both in responses to individual questions and in the overall score in the following domains: equal access to opportunities, work-life balance, and leader support, and in the total score for the CCWAS. CONCLUSIONS: Our survey is the first of its kind completed during the COVID-19 pandemic at an NCI-designated Cancer Center, in which myriad factors contributed to burnout and workplace challenges. These results point to specific issues that detract from the success of women pursuing careers in academic oncology. Identifying these issues can be used to design and implement solutions to improve workforce culture, mitigate gender bias, and retain faculty.

PURPOSE: The effect of climate-driven events, such as wildfires, on health care delivery and cancer care is a growing concern. Patients with cancer undergoing radiation therapy are particularly vulnerable to treatment interruptions, which have a direct effect on survival. We report the results of a study characterizing the effect of wildfires on radiation oncology clinics and their patients. METHODS AND MATERIALS: A survey of California radiation oncologists was used to evaluate emergency preparedness and the effect of wildfires on the delivery of radiation therapy services between 2017 and 2022. Descriptive statistics and Pearsons χ2 tests were performed to investigate potential relationships between provider characteristics, practice settings, and perceptions of the effect of wildfire events. California Department of Forestry and Fire Protection data were employed to map the geographic distribution of wildfires to clinic locations. RESULTS: Response rate was 12.3% (51/415 radiation oncologists), representing 25% of clinics (43/176) in 41% (24/58) of California counties. Sixty-one percent (31/51) of respondents reported being affected by a wildfire, 2 of which are rural clinics (100%, 2/2) and 29 are (59%, 29/49) metropolitan practices. Of these, 18% (9/51) reported a clinic closure, and 29% (15/51) reported staffing shortages. Respondents reported effects on patients, including having to evacuate (55%, 28/51), cancel/reschedule treatments (53%, 27/51), and experiencing physical, mental, or financial hardship due to wildfires (45%, 23/51). Respondents described effects on clinical operations, including being forced to transfer patients (24%, 12/51), transportation interruptions (37%, 19/51), regional/community evacuations (35%, 18/51), and physical/mental health effects (27%, 14/51) on clinic personnel. Less than half of the respondents (47%, 24/51) reported their workplace had a wildfire emergency preparedness plan. Additionally, geographic analysis revealed that 100% (176/176) of clinics were located within 25 miles of a wildfire. CONCLUSIONS: This study highlights the effects of wildfires on radiation oncology clinics and patients and underscores the need for emergency preparedness planning to minimize the consequences of such disasters.

PURPOSE: Having dedicated MRI scanners within radiation oncology departments may present unexpected challenges since radiation oncologists and radiation therapists are generally not trained in this modality and there are potential patient safety concerns. This study retrospectively reviews the incidental findings and safety events that were observed at a single institution during introduction of MRI sim for head and neck radiotherapy planning. METHODS: Consecutive patients from March 1, 2020, to May 31, 2022, who were scheduled for MRI sim after having completed CT simulation for head and neck radiotherapy were included for analysis. Patients first underwent a CT simulation with a thermoplastic mask and in most cases with an intraoral stent. The same setup was then reproduced in the MRI simulator. Safety events were instances where scheduled MRI sims were not completed due to the MRI technologist identifying MRI-incompatible devices or objects at the time of sim. Incidental findings were identified during weekly quality assurance rounds as a joint enterprise of head and neck radiation oncology and neuroradiology. Categorical variables between completed and not completed MRI sims were compared using the Chi-Square test and continuous variables were compared using the Mann-Whitney U test with a p-value of

BACKGROUND: Magnetic resonance image only (MRI-only) simulation for head and neck (H&N) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic computed tomography (sCT) is generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCT. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI-only RT planning or compensatory methods for accurate dosimetric calculation. PURPOSE: The aim of this study was to investigate if Hounsfield unit (HU) voxel misassignments from sCT images result in dosimetric errors in clinical treatment plans. METHODS: Fourteen H&N cancer patients undergoing same-day CT and 3T MRI simulation were retrospectively identified. MRI was deformed to the CT using multimodal deformable image registration. sCTs were generated from T1w DIXON MRIs using a commercially available deep learning-based generator (MRIplanner, Spectronic Medical AB, Helsingborg, Sweden). Tissue voxel assignment was quantified by creating a CT-derived HU threshold contour. CT/sCT HU differences for anatomical/target contours and tissue classification regions including air (500 HU) were quantified. t-test was used to determine if sCT/CT HU differences were significant. The frequency of structures that had a HU difference > 80 HU (the CT window-width setting for intra-cranial structures) was computed to establish structure classification accuracy. Clinical intensity modulated radiation therapy (IMRT) treatment plans created on CT were retrospectively recalculated on sCT images and compared using the gamma metric. RESULTS: The mean ratio of sCT HUs relative to CT for air, adipose tissue, soft tissue, spongy and cortical bone were 1.7 ± 0.3, 1.1 ± 0.1, 1.0 ± 0.1, 0.9 ± 0.1 and 0.8 ± 0.1 (value of 1 indicates perfect agreement). T-tests (significance set at t = 0.05) identified differences in HU values for air, spongy and cortical bone in sCT images compared to CT. The structures with sCT/CT HU differences > 80 HU of note were the left and right (L/R) cochlea and mandible (>79% of the tested cohort), the oral cavity (for 57% of the tested cohort), the epiglottis (for 43% of the tested cohort) and the L/R TM joints (occurring > 29% of the cohort). In the case of the cochlea and TM joints, these structures contain dense bone/air interfaces. In the case of the oral cavity and mandible, these structures suffer the additional challenge of being positionally altered in CT versus MRI simulation (due to a non-MR safe immobilizing bite block requiring absence of bite block in MR). Finally, the epiglottis HU assignment suffers from its small size and unstable positionality. Plans recalculated on sCT yielded global/local gamma pass rates of 95.5% ± 2% (3 mm, 3%) and 92.7% ± 2.1% (2 mm, 2%). The largest mean differences in D95, Dmean , D50 dose volume histogram (DVH) metrics for organ-at-risk (OAR) and planning tumor volumes (PTVs) were 2.3% ± 3.0% and 0.7% ± 1.9% respectively. CONCLUSIONS: In this cohort, HU differences of CT and sCT were observed but did not translate into a reduction in gamma pass rates or differences in average PTV/OAR dose metrics greater than 3%. For sites such as the H&N where there are many tissue interfaces we did not observe large scale dose deviations but further studies using larger retrospective cohorts are merited to establish the variation in sCT dosimetric accuracy which could help to inform QA limits on clinical sCT usage.

Abstract Nudging individuals without obvious symptoms of non-communicable diseases (NCDs) to undergo a health screening remains a challenge, especially in middle-income countries, where NCD awareness is low but the incidence is high. We assess whether an awareness campaign implemented on Facebook can encourage individuals in Indonesia to undergo an online diabetes self-screening. We use Facebook’s advertisement function to randomly distribute graphical ads related to the risk and consequences of diabetes. Depending on their risk score, participants receive a recommendation to undergo a professional screening. We were able to reach almost 300,000 individuals in only three weeks. More than 1400 individuals completed the screening, inducing costs of about US$0.75 per person. The two ads labeled “diabetes consequences” and “shock” outperform all other ads. A follow-up survey shows that many high-risk respondents have scheduled a professional screening. A cost-effectiveness analysis suggests that our campaign can diagnose an additional person with diabetes for about US$9.

Abstract Tuberculosis (TB) preventive treatment (TPT) effectively prevents the progression from TB infection to TB disease. This study explores factors associated with TPT non-completion in Cambodia using 6-years programmatic data (2018–2023) retrieved from the TB Management Information System (TB-MIS). Out of 14,262 individuals with latent TB infection (LTBI) initiated with TPT, 299 (2.1%) did not complete the treatment. Individuals aged between 15–24 and 25–34 years old were more likely to not complete the treatment compared to those aged

Abstract We propose a method to estimate the household secondary attack rate (hSAR) of COVID-19 in the United Kingdom based on activity on the social media platform X, formerly known as Twitter. Conventional methods of hSAR estimation are resource intensive, requiring regular contact tracing of COVID-19 cases. Our proposed framework provides a complementary method that does not rely on conventional contact tracing or laboratory involvement, including the collection, processing, and analysis of biological samples. We use a text classifier to identify reports of people tweeting about themselves and/or members of their household having COVID-19 infections. A probabilistic analysis is then performed to estimate the hSAR based on the number of self or household, and self and household tweets of COVID-19 infection. The analysis includes adjustments for a reluctance of Twitter users to tweet about household members, and the possibility that the secondary infection was not acquired within the household. Experimental results for the UK, both monthly and weekly, are reported for the period from January 2020 to February 2022. Our results agree with previously reported hSAR estimates, varying with the primary variants of concern, e.g. delta and omicron. The serial interval (SI) is based on the time between the two tweets that indicate a primary and secondary infection. Experimental results, though larger than the consensus, are qualitatively similar. The estimation of hSAR and SI using social media data constitutes a new tool that may help in characterizing, forecasting and managing outbreaks and pandemics in a faster, affordable, and more efficient manner.

BackgroundDigital and mobile health interventions using personalization via reinforcement learning algorithms have the potential to reach large number of people to support physical activity and help manage diabetes and depression in daily life. ObjectiveThe Diabetes and Mental Health Adaptive Notification and Tracking Evaluation (DIAMANTE) study tested whether a digital physical activity intervention using personalized text messaging via reinforcement learning algorithms could increase step counts in a diverse, multilingual sample of people with diabetes and depression symptoms. MethodsFrom January 2020 to June 2022, participants were recruited from 4 San Francisco, California–based public primary care clinics and through web-based platforms to participate in the 24-week randomized controlled trial. Eligibility criteria included English or Spanish language preference and a documented diagnosis of diabetes and elevated depression symptoms. The trial had 3 arms: a Control group receiving a weekly mood monitoring message, a Random messaging group receiving randomly selected feedback and motivational text messages daily, and an Adaptive messaging group receiving text messages selected by a reinforcement learning algorithm daily. Randomization was performed with a 1:1:1 allocation. The primary outcome, changes in daily step counts, was passively collected via a mobile app. The primary analysis assessed changes in daily step count using a linear mixed-effects model. An a priori subanalysis compared the primary step count outcome within recruitment samples. ResultsIn total, 168 participants were analyzed, including those with 24% (40/168) Spanish language preference and 37.5% (63/168) from clinic-based recruitment. The results of the linear mixed-effects model indicated that participants in the Adaptive arm cumulatively gained an average of 3.6 steps each day (95% CI 2.45-4.78; P

The purpose of this study was to determine the negative predictive value (NPV) of a 12- to 14-wk posttreatment PET/CT for 2-y progression-free survival (PFS) and locoregional control (LRC) in patients with p16-positive locoregionally advanced oropharyngeal cancer (LA-OPC). Study was a secondary endpoint in NRG-HN002, a noncomparative phase II trial in p16-positive LA-OPC, stage T1-T2, N1-N2b or T3, N0-N2b, and ≤10 pack-year smoking. Patients were randomized in a 1:1 ratio to reduced-dose intensity-modulated radiotherapy (IMRT) with or without cisplatin. Methods: PET/CT scans were reviewed centrally. Tumor response evaluations for the primary site, right neck, and left neck were performed using a 5-point ordinal scale (Hopkins criteria). Overall scores were then assigned as negative, positive, or indeterminate. Patients with a negative score for all 3 evaluation sites were given an overall score of negative. The hypotheses were NPV for PFS and LRC at 2-y posttreatment ≤ 90% versus >90% (1-sided P value, 0.10). Results: A total of 316 patients were enrolled, of whom 306 were randomized and eligible. Of these, 131 (42.8%) patients consented to a posttherapy PET/CT, and 117 (89.3%) patients were eligible for PET/CT analysis. The median time from the end of treatment to PET/CT scan was 94 d (range, 52-139 d). Estimated 2-y PFS and LRC rates in the analysis subgroup were 91.3% (95% CI, 84.6, 95.8%) and 93.8% (95% CI, 87.6, 97.5%), respectively. Posttreatment scans were negative for residual tumor for 115 patients (98.3%) and positive for 2 patients (1.7%). NPV for 2-y PFS was 92.0% (90% lower confidence bound [LCB] 87.7%; P = 0.30) and for LRC was 94.5% (90% LCB 90.6%; P = 0.07). Conclusion: In the context of deintensification with reduced-dose radiation, the NPV of a 12- to 14-wk posttherapy PET/CT for 2-y LRC is estimated to be >90%, similar to that reported for patients receiving standard chemoradiation. However, there is insufficient evidence to conclude that the NPV is >90% for PFS.

Abstract Background Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses. Methods This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235. Results The cohort had a median age of 53 years old (range 20–81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral. Conclusions Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes.

BACKGROUND: Anaplastic thyroid cancer is a rare and aggressive cancer with no standard radiotherapy-based local treatment. Based on data suggesting synergy between pazopanib and paclitaxel in anaplastic thyroid cancer, NRG Oncology did a double-blind, placebo-controlled, randomised phase 2 clinical trial comparing concurrent paclitaxel and intensity-modulated radiotherapy (IMRT) with the addition of pazopanib or placebo with the aim of improving overall survival in this patient population. METHODS: Eligible patients were aged 18 years or older with a pathological diagnosis of anaplastic thyroid cancer, any TNM stage, Zubrod performance status of 0-2, no recent haemoptysis or bleeding, and no brain metastases. Patients were enrolled from 34 centres in the USA. Initially, a run-in was done to establish safety. In the randomised phase 2 trial, patients in the experimental group (pazopanib) received 2-3 weeks of weekly paclitaxel (80 mg/m2) intravenously and daily pazopanib suspension 400 mg orally followed by concurrent weekly paclitaxel (50 mg/m2), daily pazopanib (300 mg), and IMRT 66 Gy given in 33 daily fractions (2 Gy fractions). In the control group (placebo), pazopanib was replaced by matching placebo. Patients were randomly assigned (1:1) to the two treatment groups by permuted block randomisation by NRG Oncology with stratification by metastatic disease. All investigators, patients, and funders of the study were masked to group allocation. The primary endpoint was overall survival in the intention-to-treat population. Safety was assessed in all patients who received at least one dose of study treatment. This trial is registered with Clinicaltrials.gov, NCT01236547, and is complete. FINDINGS: The safety run-showed the final dosing regimen to be safe based on two out of nine participants having adverse events of predefined concern. Between June 23, 2014, and Dec 30, 2016, 89 patients were enrolled to the phase 2 trial, of whom 71 were eligible (36 in the pazopanib group and 35 in the placebo group; 34 [48%] males and 37 [52%] females). At the final analysis (data cutoff March 9, 2020), with a median follow-up of 2·9 years (IQR 0·002-4·0), 61 patients had died. Overall survival was not significantly improved with pazopanib versus placebo, with a median overall survival of 5·7 months (95% CI 4·0-12·8) in the pazopanib group versus 7·3 months (4·3-10·6) in the placebo group (hazard ratio 0·86, 95% CI 0·52-1·43; one-sided log-rank p=0·28). 1-year overall survival was 37·1% (95% CI 21·1-53·2) in the pazopanib group and 29·0% (13·2-44·8) in the placebo group. The incidence of grade 3-5 adverse events did not differ significantly between the treatment groups (pazopanib 88·9% [32 of 36 patients] and placebo 85·3% [29 of 34 patients]; p=0·73). The most common clinically significant grade 3-4 adverse events in the 70 eligible treated patients (36 in the pazopanib group and 34 in the placebo group) were dysphagia (13 [36%] vs 10 [29%]), radiation dermatitis (8 [22%] vs 13 [38%]), increased alanine aminotransferase (12 [33%] vs none), increased aspartate aminotransferase (eight [22%] vs none), and oral mucositis (five [14%] vs eight [24%]). Treatment-related serious adverse events were reported for 16 (44%) patients on pazopanib and 12 (35%) patients on placebo. The most common serious adverse events were dehydration and thromboembolic event (three [8%] each) in patients on pazopanib and oral mucositis (three [8%]) in those on placebo. There was one treatment-related death in each group (sepsis in the pazopanib group and pneumonitis in the placebo group). INTERPRETATION: To our knowledge, this study is the largest randomised anaplastic thyroid cancer study that has completed accrual showing feasibility in a multicenter NCI National Clinical Trials Network setting. Although no significant improvement in overall survival was recorded in the pazopanib group, the treatment combination was shown to be feasible and safe, and hypothesis-generating data that might warrant further investigation were generated. FUNDING: National Cancer Institute and Novartis.

Oriented cell divisions balance self-renewal and differentiation in stratified epithelia such as the skin epidermis. During peak epidermal stratification, the distribution of division angles among basal keratinocyte progenitors is bimodal, with planar and perpendicular divisions driving symmetric and asymmetric daughter cell fates, respectively. An apically restricted, evolutionarily conserved spindle orientation complex that includes the scaffolding protein LGN/Pins/Gpsm2 plays a central role in promoting perpendicular divisions and stratification, but why only a subset of cell polarize LGN is not known. Here, we demonstrate that the LGN paralog, AGS3/Gpsm1, is a novel negative regulator of LGN and inhibits perpendicular divisions. Static and ex vivo live imaging reveal that AGS3 overexpression displaces LGN from the apical cortex and increases planar orientations, while AGS3 loss prolongs cortical LGN localization and leads to a perpendicular orientation bias. Genetic epistasis experiments in double mutants confirm that AGS3 operates through LGN. Finally, clonal lineage tracing shows that LGN and AGS3 promote asymmetric and symmetric fates, respectively, while also influencing differentiation through delamination. Collectively, these studies shed new light on how spindle orientation influences epidermal stratification.

TP53 mutation is the most frequent genetic event in head and neck squamous cell carcinoma (HNSCC), found in more than 80% of patients with human papillomavirus-negative disease. As mutations in the TP53 gene are associated with worse outcomes in HNSCC, novel therapeutic approaches are needed for patients with TP53-mutated tumors. The National Cancer Institute sponsored a Clinical Trials Planning Meeting to address the issues of identifying and developing clinical trials for patients with TP53 mutations. Subcommittees, or breakout groups, were tasked with developing clinical studies in both the locally advanced and recurrent and/or metastatic (R/M) disease settings as well as considering signal-seeking trial designs. A fourth breakout group was focused on identifying and standardizing biomarker integration into trial design; this information was provided to the other breakout groups prior to the meeting to aid in study development. A total of 4 concepts were prioritized to move forward for further development and implementation. This article summarizes the proceedings of the Clinical Trials Planning Meeting with the goal of developing clinical trials for patients with TP53-mutant HNSCC that can be conducted within the National Clinical Trials Network.

Abstract Text messaging can promote healthy behaviors, like adherence to medication, yet its effectiveness remains modest, in part because message content is rarely personalized. Reinforcement learning has been used in consumer technology to personalize content but with limited application in healthcare. We tested a reinforcement learning program that identifies individual responsiveness (“adherence”) to text message content and personalizes messaging accordingly. We randomized 60 individuals with diabetes and glycated hemoglobin A1c [HbA1c] ≥ 7.5% to reinforcement learning intervention or control (no messages). Both arms received electronic pill bottles to measure adherence. The intervention improved absolute adjusted adherence by 13.6% (95%CI: 1.7%–27.1%) versus control and was more effective in patients with HbA1c 7.5-

Suicide, one of the top causes of life lost in developed countries, is a major health problem, especially today, with the dramatic increase in mental health difficulties that was triggered during the Coronavirus pandemic (COVID-19). Opportunely, the recent emergence of internet-based crowdsourcing platforms (e.g., Amazon’s Mechanical Turk) may accelerate research on suicide prevention, however, this type of suicide research online involves a difficult ethical challenge: how to keep participants’ safe without compromising their privacy. To address this ethical challenge, a consortium of experts from multiple research institutions was assembled. The consortium discussed the advantages and disadvantages for participants involved in crowdsourcing-based studies that address suicide risk. This discussion resulted in a consensual step-by-step protocol for researchers who wish to conduct suicide research online, using the crowdsourcing platforms. This article provides a detailed description of the protocol and outlines key ethical arguments that led to its formulation. Unresolved issues are discussed as well and other researchers are encouraged to implement the proposed protocol and suggest further improvements. It is our hope that the current protocol will facilitate the research on large and diverse populations online and thus contribute to the global efforts to reduce suicide rates around the world.