An assessment of the association between patient characteristics and timely lung cancer treatment.

PURPOSE: Prior data have demonstrated relationships between patient characteristics, the use of surgery to treat lung cancer, and the timeliness of treatment. Our study examines whether these relationships were observable in 2019 in patients with Medicare Advantage health plans being treated for lung cancer. METHODS: Claims data pertaining to patients with Medicare Advantage health plans who had received radiation therapy (RT) or surgery to treat lung cancer within 90 days of diagnostic imaging were extracted. Other databases were used to determine patients' demographics, comorbidities, the urbanicity of their ZIP code, the median income of their ZIP code, and whether their treatment was ordered by a physician at a hospital. Multivariable logistic and Cox Proportional Hazards models were used to assess the association between patient characteristics, receipt of surgery, and time to non-systemic treatment (surgery or RT), respectively. RESULTS: A total of 2,682 patients were included in the analysis. In an adjusted analysis, patients were significantly less likely to receive surgery if their first ordering physician was based in a hospital, if they were older, if they had a history of congestive heart failure (CHF), if they had a history of chronic obstructive pulmonary disease, or if they had stage III lung cancer. Likewise, having stage III cancer was associated with significantly shorter time to treatment. CONCLUSIONS: Within a Medicare Advantage population, patient demographics were found to be significantly associated with the decision to pursue surgery, but factors other than stage were not significantly associated with time to non-systemic treatment.

Evaluating the relationship between magnetic resonance image quality metrics and deep learning-based segmentation accuracy of brain tumors.

BACKGROUND: Magnetic resonance imaging (MRI) scans are known to suffer from a variety of acquisition artifacts as well as equipment-based variations that impact image appearance and segmentation performance. It is still unclear whether a direct relationship exists between magnetic resonance (MR) image quality metrics (IQMs) (e.g., signal-to-noise, contrast-to-noise) and segmentation accuracy. PURPOSE: Deep learning (DL) approaches have shown significant promise for automated segmentation of brain tumors on MRI but depend on the quality of input training images. We sought to evaluate the relationship between IQMs of input training images and DL-based brain tumor segmentation accuracy toward developing more generalizable models for multi-institutional data. METHODS: We trained a 3D DenseNet model on the BraTS 2020 cohorts for segmentation of tumor subregions enhancing tumor (ET), peritumoral edematous, and necrotic and non-ET on MRI; with performance quantified via a 5-fold cross-validated Dice coefficient. MRI scans were evaluated through the open-source quality control tool MRQy, to yield 13 IQMs per scan. The Pearson correlation coefficient was computed between whole tumor (WT) dice values and IQM measures in the training cohorts to identify quality measures most correlated with segmentation performance. Each selected IQM was used to group MRI scans as "better" quality (BQ) or "worse" quality (WQ), via relative thresholding. Segmentation performance was re-evaluated for the DenseNet model when (i) training on BQ MRI images with validation on WQ images, as well as (ii) training on WQ images, and validation on BQ images. Trends were further validated on independent test sets derived from the BraTS 2021 training cohorts. RESULTS: For this study, multimodal MRI scans from the BraTS 2020 training cohorts were used to train the segmentation model and validated on independent test sets derived from the BraTS 2021 cohort. Among the selected IQMs, models trained on BQ images based on inhomogeneity measurements (coefficient of variance, coefficient of joint variation, coefficient of variation of the foreground patch) and the models trained on WQ images based on noise measurement peak signal-to-noise ratio (SNR) yielded significantly improved tumor segmentation accuracy compared to their inverse models. CONCLUSIONS: Our results suggest that a significant correlation may exist between specific MR IQMs and DenseNet-based brain tumor segmentation performance. The selection of MRI scans for model training based on IQMs may yield more accurate and generalizable models in unseen validation.

A novel method to guide biomarker combinations to optimize the sensitivity.

Logistic regression has demonstrated its utility in classifying binary labeled datasets through the maximum likelihood approach. However, in numerous biological and clinical contexts, the aim is often to determine coefficients that yield the highest sensitivity at the pre-specified specificity or vice versa. Therefore, the application of logistic regression is limited in such settings. To this end, we have developed an improved regression framework, SMAGS, for binary classification that, for a given specificity, finds the linear decision rule that yields the maximum sensitivity. Furthermore, we employed the method for feature selection to find the features that are satisfying the sensitivity maximization goal. We compared our method with normal logistic regression by applying it to real clinical data as well as synthetic data. In the real application data (colorectal cancer dataset), we found 14% improvement of sensitivity at 98.5% specificity. Availability and implementation: Software is made available in Python ( https://github.com/smahmoodghasemi/SMAGS ).

Cabozantinib monotherapy for advanced adrenocortical carcinoma: a single-arm, phase 2 trial.

BACKGROUND: Adrenocortical carcinoma is a rare malignancy with poor response to systemic chemotherapy. Mitotane is the only approved therapy for adrenocortical carcinoma. Cabozantinib is a multikinase inhibitor approved in multiple malignancies. This is the first prospective trial to explore the anti-tumour activity, safety, and pharmacokinetic profile of cabozantinib in patients with advanced adrenocortical carcinoma. METHODS: This investigator-initiated, single-arm, phase 2 trial in adult patients (aged ≥18 years) with advanced adrenocortical carcinoma was done at the University of Texas MD Anderson Cancer Center (Houston, TX, USA). Eligible patients had histologically confirmed adrenocortical carcinoma, were not candidates for surgery with curative intent, had measurable disease, had an estimated life expectancy of at least 3 months, and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2 with adequate organ function. Patients who had used mitotane within 6 months of study participation were required to have a serum mitotane level of less than 2 mg/L. Patients were given oral cabozantinib 60 mg daily with the option of dose reduction to manage adverse events. The primary endpoint was progression-free survival at 4 months, assessed in all patients who received at least one dose of study drug per protocol. This study is registered with ClinicalTrials.gov, NCT03370718, and is now complete. FINDINGS: Between March 1, 2018, and May 31, 2021, we enrolled 18 patients (ten males and eight females), all of whom received at least one dose of study treatment. Of the 18 patients, eight (44%) had an ECOG performance status of 0, nine (50%) patients had a performance status of 1, and one (6%) patient had a performance status of 2. Median follow-up was 36·8 months (IQR 30·2-50·3). At 4 months, 13 (72·2%; 95% CI 46·5-90·3) of 18 patients had progression-free survival and median progression-free survival was 6 months (95% CI 4·3 to not reached). One patient remains on treatment. Treatment-related adverse events of grade 3 or worse occurred in 11 (61%) of 18 patients. The most common grade 3 adverse events were lipase elevation (three [17%] of 18 patients), elevated γ-glutamyl transferase concentrations (two [11%] patients), elevated alanine aminotransferase concentrations (two [11%] patients), hypophosphatemia (two [11%] patients), and hypertension (two [11%] patients). One (6%) of 18 patients had grade 4 hypertension. No treatment related deaths occurred on study. INTERPRETATION: Cabozantinib in advanced adrenocortical carcinoma showed promising efficacy with a manageable and anticipated safety profile. Further prospective studies with cabozantinib alone and in combination with immune checkpoint therapy are ongoing. FUNDING: Exelixis.

Cabozantinib in patients with unresectable and progressive metastatic phaeochromocytoma or paraganglioma (the Natalie Trial): a single-arm, phase 2 trial.

BACKGROUND: Metastatic phaeochromocytomas and paragangliomas (MPPGs) are orphan diseases. Up to 50% of MPPGs are associated with germline pathogenic variants of the SDHB gene. These tumours and many non-familial MPPGs exhibit a phenotype that is characterised by abnormal angiogenesis. We aimed to assess the activity and safety of cabozantinib, an antiangiogenic multi-tyrosine kinase inhibitor, in patients with MPPGs. METHODS: The Natalie Trial is a single-arm, phase 2 clinical trial being conducted at The University of Texas MD Anderson Cancer Center (Houston, TX, USA). Patients aged 18 years or older with histologically confirmed, progressive, and unresectable MPPGs, with an Eastern Cooperative Oncology Group performance status of 0-2, were treated with oral cabozantinib 60 mg/day. The primary endpoint was the investigator-assessed overall response rate per the Response Evaluation Criteria in Solid Tumours version 1.1 criteria. All outcomes were assessed in all evaluable participants who received any amount of study treatment. The trial is registered with ClinicalTrials.gov (NCT02302833) and is active but not recruiting. FINDINGS: From March 10, 2015, to May 11, 2021, 17 patients (13 male participants and four female participants) were enrolled. The median follow-up was 25 months (IQR 18-49). The overall response rate was 25·0% (95% CI 7·3-52·4; four of 16 patients). Seven grade 3 adverse events were reported in six patients, including single cases of hand-and-foot syndrome, hypertension, rectal fistula, QT prolongation, and asymptomatic hypomagnesaemia, and two cases of asymptomatic elevations of amylase and lipase. There were no grade 4 adverse events and no patient died on-study. INTERPRETATION: Cabozantinib shows promising activity in patients with MPPGs. FUNDING: Team NAT Foundation, Margaret Cazalot, and Clarence P Cazalot.

Healthcare provider perceptions and reported practices regarding opioid prescription for patients with chronic cancer pain.

PURPOSE: Data indicates that clinicians might be under-prescribing opioids for patients with chronic cancer pain, and this could impact adequate pain management. Few studies have sought to understand healthcare provider (HCP) perceptions and practices regarding the prescription of opioids for chronic cancer pain. We assessed HCP perceptions and practices regarding opioid prescription for patients with chronic cancer pain since the onset of the COVID-19 pandemic. METHODS: An anonymous cross-sectional survey was conducted among 186 HCPs who attended an opioid educational event in April 2021 and 2022. RESULTS: Sixty-one out of 143 (44%) opioid prescribers reported reluctance to prescribe opioids for chronic cancer pain. In a multivariate logistic model, younger participants (log OR - 0.04, 95% CI - 0.085, - 0.004; p = 0.033) and pain medicine clinicians (log OR - 1.89, CI - 3.931, - 0.286; p = 0.034) were less reluctant, whereas providers who worry about non-medical opioid use were more reluctant to prescribe opioids (log OR 1.58 95% CI 0.77-2.43; p < 0.001). Fifty-three out of 143 (37%) prescribers had experienced increased challenges regarding opioid dispensing at pharmacies, and 84/179 (47%) of all respondents reported similar experience by their patients. Fifty-four out of 178(30%) were aware of opioid-related harmful incidents to patients or their families, including incidents attributed to opioid misuse by a household or family member. CONCLUSION: A considerable number of opioid prescribers were reluctant to prescribe opioids for patients with chronic cancer pain. Many reported challenges regarding dispensing of opioids at the pharmacies. These may be unintended consequences of policies to address the opioid crisis. Future measures should focus on addressing regulatory barriers without undermining the gains already made to combat the opioid crisis.

mRNA-based precision targeting of neoantigens and tumor-associated antigens in malignant brain tumors.

BACKGROUND: Despite advancements in the successful use of immunotherapy in treating a variety of solid tumors, applications in treating brain tumors have lagged considerably. This is due, at least in part, to the lack of well-characterized antigens expressed within brain tumors that can mediate tumor rejection; the low mutational burden of these tumors that limits the abundance of targetable neoantigens; and the immunologically "cold" tumor microenvironment that hampers the generation of sustained and productive immunologic responses. The field of mRNA-based therapeutics has experienced a boon following the universal approval of COVID-19 mRNA vaccines. mRNA-based immunotherapeutics have also garnered widespread interest for their potential to revolutionize cancer treatment. In this study, we developed a novel and scalable approach for the production of personalized mRNA-based therapeutics that target multiple tumor rejection antigens in a single therapy for the treatment of refractory brain tumors. METHODS: Tumor-specific neoantigens and aberrantly overexpressed tumor-associated antigens were identified for glioblastoma and medulloblastoma tumors using our cancer immunogenomics pipeline called Open Reading Frame Antigen Network (O.R.A.N). Personalized tumor antigen-specific mRNA vaccine was developed for each individual tumor model using selective gene capture and enrichment strategy. The immunogenicity and efficacy of the personalized mRNA vaccines was evaluated in combination with anti-PD-1 immune checkpoint blockade therapy or adoptive cellular therapy with ex vivo expanded tumor antigen-specific lymphocytes in highly aggressive murine GBM models. RESULTS: Our results demonstrate the effectiveness of the antigen-specific mRNA vaccines in eliciting robust anti-tumor immune responses in GBM hosts. Our findings substantiate an increase in tumor-infiltrating lymphocytes characterized by enhanced effector function, both intratumorally and systemically, after antigen-specific mRNA-directed immunotherapy, resulting in a favorable shift in the tumor microenvironment from immunologically cold to hot. Capacity to generate personalized mRNA vaccines targeting human GBM antigens was also demonstrated. CONCLUSIONS: We have established a personalized and customizable mRNA-therapeutic approach that effectively targets a plurality of tumor antigens and demonstrated potent anti-tumor response in preclinical brain tumor models. This platform mRNA technology uniquely addresses the challenge of tumor heterogeneity and low antigen burden, two key deficiencies in targeting the classically immunotherapy-resistant CNS malignancies, and possibly other cold tumor types.

Modulating a prebiotic food source influences inflammation and immune-regulating gut microbes and metabolites: insights from the BE GONE trial.

BACKGROUND: Accessible prebiotic foods hold strong potential to jointly target gut health and metabolic health in high-risk patients. The BE GONE trial targeted the gut microbiota of obese surveillance patients with a history of colorectal neoplasia through a straightforward bean intervention. METHODS: This low-risk, non-invasive dietary intervention trial was conducted at MD Anderson Cancer Center (Houston, TX, USA). Following a 4-week equilibration, patients were randomized to continue their usual diet without beans (control) or to add a daily cup of study beans to their usual diet (intervention) with immediate crossover at 8-weeks. Stool and fasting blood were collected every 4 weeks to assess the primary outcome of intra and inter-individual changes in the gut microbiome and in circulating markers and metabolites within 8 weeks. This study was registered on ClinicalTrials.gov as NCT02843425, recruitment is complete and long-term follow-up continues. FINDINGS: Of the 55 patients randomized by intervention sequence, 87% completed the 16-week trial, demonstrating an increase on-intervention in diversity [n = 48; linear mixed effect and 95% CI for inverse Simpson index: 0.16 (0.02, 0.30); p = 0.02] and shifts in multiple bacteria indicative of prebiotic efficacy, including increased Faecalibacterium, Eubacterium and Bifidobacterium (all p < 0.05). The circulating metabolome showed parallel shifts in nutrient and microbiome-derived metabolites, including increased pipecolic acid and decreased indole (all p < 0.002) that regressed upon returning to the usual diet. No significant changes were observed in circulating lipoproteins within 8 weeks; however, proteomic biomarkers of intestinal and systemic inflammatory response, fibroblast-growth factor-19 increased, and interleukin-10 receptor-α decreased (p = 0.01). INTERPRETATION: These findings underscore the prebiotic and potential therapeutic role of beans to enhance the gut microbiome and to regulate host markers associated with metabolic obesity and colorectal cancer, while further emphasizing the need for consistent and sustainable dietary adjustments in high-risk patients. FUNDING: This study was funded by the American Cancer Society.

Conceptualizing a less paranoid schizophrenia.

Schizophrenia stands as one of the most studied and storied disorders in the history of clinical psychology; however, it remains a nexus of conflicting and competing conceptualizations. Patients endure great stigma, poor treatment outcomes, and condemnatory prognosis. Current conceptualizations suffer from unstable categorical borders, heterogeneity in presentation, outcome and etiology, and holes in etiological models. Taken in aggregate, research and clinical experience indicate that the class of psychopathologies oriented toward schizophrenia are best understood as spectra of phenomenological, cognitive, and behavioral modalities. These apparently taxonomic expressions are rooted in normal human personality traits as described in both psychodynamic and Five Factor personality models, and more accurately represent explicable distress reactions to biopsychosocial stress and trauma. Current categorical approaches are internally hampered by axiomatic bias and systemic inertia rooted in the foundational history of psychological inquiry; however, when such axioms are schematically decentralized, convergent cross-disciplinary evidence outlines a more robust explanatory construct. By reconceptualizing these disorders under a dimensional and cybernetic model, the aforementioned issues of instability and inaccuracy may be resolved, while simultaneously opening avenues for both early detection and intervention, as well as for more targeted and effective treatment approaches.

Healthcare provider perceptions and reported practices regarding opioid prescription for patients with chronic pain.

PURPOSE: Data indicates that clinicians might be under-prescribing opioids for patients with chronic cancer pain, and this could impact adequate chronic pain management. Few studies have sought to understand healthcare provider (HCP) perceptions and practices regarding the prescription of opioids for chronic pain. We assessed HCP perceptions and practices regarding opioid prescription for patients with chronic pain since the onset of the COVID-19 pandemic. METHODS: An anonymous cross-sectional survey was conducted among 186 HCPs who attended an opioid educational event in April 2021 and 2022. RESULTS: 61/143(44%) opioid prescribers reported reluctance to prescribe opioids for chronic pain. In a multivariate logistic model, younger participants (log OR -0.04, 95% CI: -0.085, -0.004; p = 0.033) and pain medicine clinicians (log OR -1.89, CI: -3.931, -0.286; p = 0.034) were less reluctant, whereas providers who worry about non-medical opioid use (NMOU) were more reluctant to prescribe opioids (log OR 1.58 95% CI: 0.77-2.43; p < 0.001). 53/143(37%) respondents had experienced increased challenges regarding opioid dispensing at pharmacies, and 84/179(47%) reported similar experience by their patients. 54/178(30%) HCPs were aware of opioid-related harmful incidents to patients or their families, including incidents attributed to opioid misuse by a household or family member. CONCLUSION: A significant number of opioid prescribers were reluctant to prescribe opioids for patients with chronic pain. Many reported challenges regarding dispensing of opioids at the pharmacies. These may be unintended consequences of policies to address the opioid crisis. Future measures should focus on addressing regulatory barriers without undermining the gains already made to combat the opioid crisis.

Lung Cancer Treatment Trends During the Coronavirus Disease 2019 (COVID-19) Pandemic: A Claims and Order Data Analysis (2019-2021).

Introduction: Lung cancer is treated using systemic therapy, radiation therapy (RT), and surgery. This study evaluates how utilization of these modalities and cancer stage at initial treatment shifted from 2019 to 2021. Methods: Claims for lung cancer treatment were extracted from the database of a national health care organization offering Medicare Advantage health plans and paired with enrollment data to determine utilization rates. Seasonally adjusted rates were trended, with monotonicity evaluated using Mann-Kendall tests. Using contemporaneous prior authorization order data, the association between year and the patient's cancer stage at the time of the initial RT or surgery order was evaluated through univariable and multivariable analyses. Results: The study considered 140.9 million beneficiary-months of data. There were negative and significantly monotonic trends in utilization of RT (p = 0.033) and systematic therapy (p = 0.003) for initial treatment between January 2020 and December 2021. Analysis of RT and surgery order data revealed that the patients were significantly (p < 0.001) more likely to have advanced (stage III or IV) cancer at the time of their surgery order in 2020 and 2021 than in 2019. After adjusting for urbanicity, age, and local income, a significant relationship between year of the initial order and presence of advanced cancer at the time of ordering was found for surgery orders placed in 2020 (p < 0.001) and 2021 (p < 0.01), but not for RT orders. Conclusions: There was a per-capita reduction in lung cancer treatment in 2020 and 2021, and patients receiving initial orders for surgery after the onset of the pandemic had more advanced cancer.

A blood-based metabolomic signature predictive of risk for pancreatic cancer.

Emerging evidence implicates microbiome involvement in the development of pancreatic cancer (PaCa). Here, we investigate whether increases in circulating microbial-related metabolites associate with PaCa risk by applying metabolomics profiling to 172 sera collected within 5 years prior to PaCa diagnosis and 863 matched non-subject sera from participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cohort. We develop a three-marker microbial-related metabolite panel to assess 5-year risk of PaCa. The addition of five non-microbial metabolites further improves 5-year risk prediction of PaCa. The combined metabolite panel complements CA19-9, and individuals with a combined metabolite panel + CA19-9 score in the top 2.5th percentile have absolute 5-year risk estimates of >13%. The risk prediction model based on circulating microbial and non-microbial metabolites provides a potential tool to identify individuals at high risk of PaCa that would benefit from surveillance and/or from potential cancer interception strategies.

Detection method has independent prognostic significance in the PLCO lung screening trial.

Prognostic models in cancer use patient demographic and tumor characteristics to predict survival and dynamic disease prognosis. Past work in breast cancer has shown that cancer detection method, screen-detected or symptom-detected, has prognostic significance. We investigate this phenomenon in the lung component of the Prostate, Lung, Colorectal, and Ovarian (PLCO) screening trial. Patients were randomized to intervention, receiving four annual chest x-rays (CXRs), or to control, receiving usual care. Patients were followed for a total of approximately 13 years. In PLCO, lung cancer detection method has independent prognostic value exceeding that of variables commonly used in lung cancer prognostic models, including sex, histology, and age. Results are robust to cohort selection and type of predictive model. These results imply that detection method should be considered when developing prognostic models in lung cancer studies, and cancer registries should routinely collect cancer detection method.

An assessment of the association between patient race and prior authorization program determinations in the context of radiation therapy.

BACKGROUND: When a physician determines that a patient needs radiation therapy (RT), they submit an RT order to a prior authorization program which assesses guideline-concordance. A rule-based clinical decision support system (CDSS) evaluates whether the order is appropriate or potentially non-indicated. If potentially non-indicated, a board-certified oncologist discusses the order with the ordering physician. After discussion, the order is authorized, modified, withdrawn, or recommended for denial. Although patient race is not captured during ordering, bias prior to and during ordering, or during the discussion, may influence outcomes. This study evaluated if associations existed between race and order determinations by the CDSS and by the overall prior authorization program. METHODS: RT orders placed in 2019, pertaining to patients with Medicare Advantage health plans from one national organization, were analyzed. The association between race and prior authorization outcomes was examined for RT orders for all cancers, and then separately for breast, lung, and prostate cancers. Analyses controlled for the patient's age, urbanicity, and the median income in the patient's ZIP code. Adjusted analyses were conducted on unmatched and racially-matched samples. RESULTS: Of the 10,145 patients included in the sample, 8,061 (79.5%) were White and 2,084 (20.5%) were Black. Race was not found to have a significant association with CDSS or prior authorization outcomes in any of the analyses. CONCLUSIONS: CDSS and prior authorization outcomes suggested similar rates of clinical appropriateness of orders for patients, regardless of race. IMPLICATIONS: Prior authorization utilizing rule-based CDSS was capable of enforcing guidelines without introducing racial bias.

Oncostatin M for characterizing the inflammatory burden and outcome of V-V ECMO in ARDS patients.

BACKGROUND: Assessing the outcome of Veno-Venous Extracorporeal Membrane Oxygenation (V-V ECMO) support remains challenging as plasma lactate (pLA), the widely used tool for this purpose, has been shown unreliable. We hypothesized that plasma oncostatin M (pOSM), a sensitive marker of leukocyte activation in infection and inflammation, could address this deficiency. METHODS: Plasma OSM levels were measured by ELISA in 30 Acute Respiratory Distress Syndrome (ARDS) patients, prior to cannulation (baseline) and decannulation. RESULTS: Based on the absolute pOSM levels at presentation, patients were separated into two groups, A and B. Patients in group A had low pOSM levels (Mean ± SD; Median, 1.1 ± 3.8; 0 pg/mL), whereas group B had high pOSM levels (1548 ± 1999; 767 pg/mL) [t-test: p < 0.01]. The percentage of pOSM levels at decannulation relative to baseline OSM levels was significantly higher in those who died (116.8 ± 68.0; 85.3%) than those who survived (47.6 ± 25.5; 48.9%) [t-test: p = 0.02; Mann-Whitney U Test: p = 0.01]. Conversely, no significant difference was observed in the percentage of pLA levels between those who died (142.9 ± 179.9; 89.8%) and those who survived (79.3 ± 34.3; 81.8%) [t-test: p = 0.31; Mann-Whitney U Test: p = 0.63]. CONCLUSION: These early findings suggested critical value of absolute and relative pOSM to characterize the inflammatory burden of ARDS patients and the outcome of their V-V ECMO support.

Case Report: Kinetics and durability of humoral and cellular response of SARS-CoV-2 messenger RNA vaccine in a lung and kidney transplant recipient.

We present a case report of a 63-year-old female health care worker who is 15 years status post double lung transplant and six years status post living related donor kidney transplant who is healthy on a chronic immunosuppression regimen including prednisone, mycophenolate, and tacrolimus who received the SARS-CoV-2 mRNA vaccine (Pfizer-BioNTech BNT162b2) primary series and had poor initial humoral response to the COVID-19 mRNA vaccine, then demonstrated a robust, sustained immune response against S1 and S2 antigens for over seven months after receiving the recommended vaccine doses, including booster dose, without developing COVID-19 or other serious adverse events. Her immune response to vaccination indicates effective formation of anti-spike T cell memory despite chronic immunosuppression. This case report provides a comprehensive characterization of her immune response to this SARS-CoV-2 vaccination series. As vaccine effectiveness data is updated, and as better understanding of immune response including hybrid immunity emerges, these findings may reassure that recipients of SOTs may be capable of durable immune responses to emerging variants of SARS-CoV-2.

Postoperative Management of Recurrence After Radiosurgery and Surgical Resection for Brain Metastases and Predicting Benefit From Adjuvant Radiation.

Stereotactic radiosurgery (SRS) is often used as upfront treatment for brain metastases. Progression or radionecrosis after SRS is common and can prompt resection. However, postoperative management strategies after resection for SRS failure vary widely, and no standard practice has been established. In this approved study, we retrospectively reviewed patients who received SRS for a brain metastasis followed by resection of the same lesion. We extracted patient-, disease-, and treatment-related variables and information on disease-related outcomes. Univariate and multivariate analyses of clinicopathologic variables were used to create a model to predict factors associated with local failure (LF). A total of 225 patients with brain metastases treated with SRS from 2009 to 2017 followed by surgical resection were identified. Overall, 65% of cases had gross total resection (GTR) on postoperative imaging review. Twenty-one patients (9.3%) received adjuvant radiation therapy to the surgical cavity, and 204 (90.7%) were observed. Of these 204 patients, 118 had GTR with evidence of tumor within the pathology specimen. With a median follow-up of 13 months after resection, 47 patients (40%) developed LF after surgery. After salvage resection of a brain metastasis initially treated with SRS, the observed LF rate was 40% among those who had a GTR and evidence of tumor on pathologic examination. This LF rate is sufficiently high that adjuvant radiation to the surgical bed after salvage resection should be considered in these cases when there is tumor in the pathology, even after a GTR.

Mortality Benefit of a Blood-Based Biomarker Panel for Lung Cancer on the Basis of the Prostate, Lung, Colorectal, and Ovarian Cohort.

PURPOSE: To investigate the utility of integrating a panel of circulating protein biomarkers in combination with a risk model on the basis of subject characteristics to identify individuals at high risk of harboring a lethal lung cancer. METHODS: Data from an established logistic regression model that combines four-marker protein panel (4MP) together with the Prostate, Lung, Colorectal, and Ovarian (PLCO) risk model (PLCOm2012) assayed in prediagnostic sera from 552 lung cancer cases and 2,193 noncases from the PLCO cohort were used in this study. Of the 552 lung cancer cases, 387 (70%) died of lung cancer. Cumulative incidence of lung cancer death and subdistributional and cause-specific hazard ratios (HRs) were calculated on the basis of 4MP + PLCOm2012 risk scores at a predefined 1.0% and 1.7% 6-year risk thresholds, which correspond to the current and former US Preventive Services Task Force screening criteria, respectively. RESULTS: When considering cases diagnosed within 1 year of blood draw and all noncases, the area under receiver operation characteristics curve estimate of the 4MP + PLCOm2012 model for risk prediction of lung cancer death was 0.88 (95% CI, 0.86 to 0.90). The cumulative incidence of lung cancer death was statistically significantly higher in individuals with 4MP + PLCOm2012 scores above the 1.0% 6-year risk threshold (modified χ2, 166.27; P < .0001). Corresponding subdistributional and lung cancer death-specific HRs for test-positive cases were 9.88 (95% CI, 6.44 to 15.18) and 10.65 (95% CI, 6.93 to 16.37), respectively. CONCLUSION: The blood-based biomarker panel in combination with PLCOm2012 identifies individuals at high risk of a lethal lung cancer.

A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes.

MOTIVATION: Multilevel molecular profiling of tumors and the integrative analysis with clinical outcomes have enabled a deeper characterization of cancer treatment. Mediation analysis has emerged as a promising statistical tool to identify and quantify the intermediate mechanisms by which a gene affects an outcome. However, existing methods lack a unified approach to handle various types of outcome variables, making them unsuitable for high-throughput molecular profiling data with highly interconnected variables. RESULTS: We develop a general mediation analysis framework for proteogenomic data that include multiple exposures, multivariate mediators on various scales of effects as appropriate for continuous, binary and survival outcomes. Our estimation method avoids imposing constraints on model parameters such as the rare disease assumption, while accommodating multiple exposures and high-dimensional mediators. We compare our approach to other methods in extensive simulation studies at a range of sample sizes, disease prevalence and number of false mediators. Using kidney renal clear cell carcinoma proteogenomic data, we identify genes that are mediated by proteins and the underlying mechanisms on various survival outcomes that capture short- and long-term disease-specific clinical characteristics. AVAILABILITY AND IMPLEMENTATION: Software is made available in an R package (https://github.com/longjp/mediateR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sleep testing during the pandemic.

BACKGROUND: The COVID-19 pandemic disrupted the U.S. healthcare system, reducing the capacity available for unrelated conditions, such as sleep disordered breathing, and increasing concerns about the safety of in-lab testing. This study characterizes how the pandemic impacted the assessment of sleep disordered breathing and use of associated services. METHODS: Sleep testing claims occurring between January 2019 and June 2021 were extracted from the database of a national healthcare organization. Utilization was trended. Logistic regressions were run to assess the association between quarter of initial testing, whether testing was followed by treatment, and whether testing was followed by a clinical visit with a diagnosis related to sleep apnea, after controlling for patient-related factors. A Cox proportional hazards model assessed factors influencing time to treatment. Finally, a logistic regression assessed factors influencing the finality of home-based testing. RESULTS: In Q2 2021, home-based testing utilization was 134% of its initial level, while in-lab and split night testing were both at 61% of initial levels. Patients receiving initial home-based testing did not significantly differ in their likelihood of treatment, but were significantly less likely to have a clinical visit for sleep apnea (P < 0.01). Patients initially tested in 2021 were treated significantly more quickly than those initially tested in Q1 2019. Home-based testing occurring in Q4 2019 or later was significantly more likely to be definitive than home-based testing occurring Q1 2019. CONCLUSIONS: Home-based sleep testing increased significantly and durably in 2020, and was associated with faster time to treatment than initial in-lab testing.