Lipoprotein(a) and Long-term In-stent Restenosis after Percutaneous Coronary Intervention.

AIM: Lipoprotein(a) [Lp(a)] has demonstrated its association with atherosclerosis and myocardial infarction. However, its role in the development of in-stent restenosis (ISR) after percutaneous coronary intervention (PCI) is not clearly established. The aim of this study is to investigate the association between Lp(a) and ISR. METHODS: A retrospective study of adult patients who underwent successful PCI between January 2006 and December 2017 at the three Mayo Clinic sites and had a preprocedural Lp(a) measurement was conducted. Patients were divided into two groups according to the serum Lp(a) concentration (high Lp(a) ≥50 mg/dl and low Lp(a) <50 mg/dl). Univariable and multivariable analyses were performed to compare risk of ISR between patients with high Lp(a) versus those with low Lp(a). RESULTS: A total of 1209 patients were included, with mean age 65.9 ±11.7 years and 71.8% were male. Median follow-up after baseline PCI was 8.8 (IQR 7.4) years. Restenosis was observed in 162 (13.4%) patients. Median serum levels of Lp(a) were significantly higher in patients affected by ISR versus non-affected cases: 27 (IQR 73.8) vs. 20 (IQR 57.5) mg/dL, p=0.008. The rate of ISR was significantly higher among patients with high Lp(a) versus patients with low Lp(a) values (17.0% vs 11.6%, p=0.010). High Lp(a) values were independently associated with ISR events (HR 1.67, 95%CI 1.18 to 2.37, p=0.004), and this association was more prominent after the first year following the PCI. CONCLUSION: Lipoprotein(a) is an independent predictor for long-term in-stent restenosis and should be considered in the evaluation of patients undergoing PCI.

The role of Lp(a) in the development of in-stent restenosis is not clearly established. In this study including 1209 patients who underwent successful percutaneous coronary intervention and had a preprocedural Lp(a) measurement between 2006 and 2017, the rates of restenosis were significantly higher among patients with high Lp(a) versus patients with low Lp(a) values and high Lp(a) concentrations were independently associated with restenosis events. Lp(a) should be considered as a risk factor for long term in-stent restenosis in the evaluation of patients undergoing percutaneous coronary intervention and assessed as a potential therapeutic target for reducing residual cardiovascular risk in this population.

CRB1-associated retinal degeneration is dependent on bacterial translocation from the gut.

The Crumbs homolog 1 (CRB1) gene is associated with retinal degeneration, most commonly Leber congenital amaurosis (LCA) and retinitis pigmentosa (RP). Here, we demonstrate that murine retinas bearing the Rd8 mutation of Crb1 are characterized by the presence of intralesional bacteria. While normal CRB1 expression was enriched in the apical junctional complexes of retinal pigment epithelium and colonic enterocytes, Crb1 mutations dampened its expression at both sites. Consequent impairment of the outer blood retinal barrier and colonic intestinal epithelial barrier in Rd8 mice led to the translocation of intestinal bacteria from the lower gastrointestinal (GI) tract to the retina, resulting in secondary retinal degeneration. Either the depletion of bacteria systemically or the reintroduction of normal Crb1 expression colonically rescued Rd8-mutation-associated retinal degeneration without reversing the retinal barrier breach. Our data elucidate the pathogenesis of Crb1-mutation-associated retinal degenerations and suggest that antimicrobial agents have the potential to treat this devastating blinding disease.

Systemic immunosuppression depletes peripheral blood regulatory B cells in patients with immune thrombocytopenia.

Regulatory B (Breg) cells are potentially implicated in the pathogenesis of immune thrombocytopenia (ITP). We analysed a prospective cohort of newly diagnosed steroid naïve ITP patients enrolled in the multicentre FLIGHT trial and found that the numbers of Bregs in their peripheral blood were similar to healthy controls. In contrast, Breg numbers were significantly reduced in ITP patients treated with systemic immunosuppression (glucocorticoids or mycophenolate mofetil). We also demonstrate that glucocorticoid treatment impairs Breg interleukin-10 production via an indirect T-cell-mediated mechanism.

The Relationship Between Cardiac Troponin in People Hospitalised for Exacerbation of COPD and Major Adverse Cardiac Events (MACE) and COPD Readmissions.

Background: No single biomarker currently risk stratifies chronic obstructive pulmonary disease (COPD) patients at the time of an exacerbation, though previous studies have suggested that patients with elevated troponin at exacerbation have worse outcomes. This study evaluated the relationship between peak cardiac troponin and subsequent major adverse cardiac events (MACE) including all-cause mortality and COPD hospital readmission, among patients admitted with COPD exacerbation. Methods: Data from five cross-regional hospitals in England were analysed using the National Institute of Health Research Health Informatics Collaborative (NIHR-HIC) acute coronary syndrome database (2008-2017). People hospitalised with a COPD exacerbation were included, and peak troponin levels were standardised relative to the 99th percentile (upper limit of normal). We used Cox Proportional Hazard models adjusting for age, sex, laboratory results and clinical risk factors, and implemented logarithmic transformation (base-10 logarithm). The primary outcome was risk of MACE within 90 days from peak troponin measurement. Secondary outcome was risk of COPD readmission within 90 days from peak troponin measurement. Results: There were 2487 patients included. Of these, 377 (15.2%) patients had a MACE event and 203 (8.2%) were readmitted within 90 days from peak troponin measurement. A total of 1107 (44.5%) patients had an elevated troponin level. Of 1107 patients with elevated troponin at exacerbation, 256 (22.8%) had a MACE event and 101 (9.0%) a COPD readmission within 90 days from peak troponin measurement. Patients with troponin above the upper limit of normal had a higher risk of MACE (adjusted HR 2.20, 95% CI 1.75-2.77) and COPD hospital readmission (adjusted HR 1.37, 95% CI 1.02-1.83) when compared with patients without elevated troponin. Conclusion: An elevated troponin level at the time of COPD exacerbation may be a useful tool for predicting MACE in COPD patients. The relationship between degree of troponin elevation and risk of future events is complex and requires further investigation.

Radiomics-based decision support tool assists radiologists in small lung nodule classification and improves lung cancer early diagnosis.

BACKGROUND: Methods to improve stratification of small (≤15 mm) lung nodules are needed. We aimed to develop a radiomics model to assist lung cancer diagnosis. METHODS: Patients were retrospectively identified using health records from January 2007 to December 2018. The external test set was obtained from the national LIBRA study and a prospective Lung Cancer Screening programme. Radiomics features were extracted from multi-region CT segmentations using TexLab2.0. LASSO regression generated the 5-feature small nodule radiomics-predictive-vector (SN-RPV). K-means clustering was used to split patients into risk groups according to SN-RPV. Model performance was compared to 6 thoracic radiologists. SN-RPV and radiologist risk groups were combined to generate "Safety-Net" and "Early Diagnosis" decision-support tools. RESULTS: In total, 810 patients with 990 nodules were included. The AUC for malignancy prediction was 0.85 (95% CI: 0.82-0.87), 0.78 (95% CI: 0.70-0.85) and 0.78 (95% CI: 0.59-0.92) for the training, test and external test datasets, respectively. The test set accuracy was 73% (95% CI: 65-81%) and resulted in 66.67% improvements in potentially missed [8/12] or delayed [6/9] cancers, compared to the radiologist with performance closest to the mean of six readers. CONCLUSIONS: SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.

Non-contrast CT synthesis using patch-based cycle-consistent generative adversarial network (Cycle-GAN) for radiomics and deep learning in the era of COVID-19.

Handcrafted and deep learning (DL) radiomics are popular techniques used to develop computed tomography (CT) imaging-based artificial intelligence models for COVID-19 research. However, contrast heterogeneity from real-world datasets may impair model performance. Contrast-homogenous datasets present a potential solution. We developed a 3D patch-based cycle-consistent generative adversarial network (cycle-GAN) to synthesize non-contrast images from contrast CTs, as a data homogenization tool. We used a multi-centre dataset of 2078 scans from 1,650 patients with COVID-19. Few studies have previously evaluated GAN-generated images with handcrafted radiomics, DL and human assessment tasks. We evaluated the performance of our cycle-GAN with these three approaches. In a modified Turing-test, human experts identified synthetic vs acquired images, with a false positive rate of 67% and Fleiss' Kappa 0.06, attesting to the photorealism of the synthetic images. However, on testing performance of machine learning classifiers with radiomic features, performance decreased with use of synthetic images. Marked percentage difference was noted in feature values between pre- and post-GAN non-contrast images. With DL classification, deterioration in performance was observed with synthetic images. Our results show that whilst GANs can produce images sufficient to pass human assessment, caution is advised before GAN-synthesized images are used in medical imaging applications.

Defining the road map to a UK national lung cancer screening programme.

Lung cancer screening with low-dose CT was recommended by the UK National Screening Committee (UKNSC) in September, 2022, on the basis of data from trials showing a reduction in lung cancer mortality. These trials provide sufficient evidence to show clinical efficacy, but further work is needed to prove deliverability in preparation for a national roll-out of the first major targeted screening programme. The UK has been world leading in addressing logistical issues with lung cancer screening through clinical trials, implementation pilots, and the National Health Service (NHS) England Targeted Lung Health Check Programme. In this Policy Review, we describe the consensus reached by a multiprofessional group of experts in lung cancer screening on the key requirements and priorities for effective implementation of a programme. We summarise the output from a round-table meeting of clinicians, behavioural scientists, stakeholder organisations, and representatives from NHS England, the UKNSC, and the four UK nations. This Policy Review will be an important tool in the ongoing expansion and evolution of an already successful programme, and provides a summary of UK expert opinion for consideration by those organising and delivering lung cancer screenings in other countries.

Factors Predicting Long-term Outcome and the Need for Surgery in Graves Orbitopathy: Extended Follow-up From the CIRTED Trial.

Graves orbitopathy is both disabling and disfiguring. Medical therapies to reduce inflammation are widely used, but there is limited trial data beyond 18 months of follow-up. METHODS: Three-year follow-up of a subset of the CIRTED trial (N = 68), which randomized patients to receive high-dose oral steroid with azathioprine/placebo and radiotherapy/sham radiotherapy. RESULTS: Data were available at 3 years from 68 of 126 randomized subjects (54%). No additional benefit was seen at 3 years for patients randomized to azathioprine or radiotherapy with regard to a binary clinical composite outcome measure (BCCOM), modified European Group on Graves' Orbitopathy score, or Ophthalmopathy Index.Clinical Activity Score (CAS), Ophthalmopathy Index, and Total Eye Score improved over 3 years (P < .001). However, quality of life at 3 years remained poor. Of 64 individuals with available surgical outcome data, 24 of 64 (37.5%) required surgical intervention. Disease duration of greater than 6 months before treatment was associated with increased need for surgery [odds ratio (OR) 16.8; 95% CI 2.95, 95.0; P = .001]. Higher baseline levels of CAS, Ophthalmopathy Index, and Total Eye Score but not early improvement in CAS were associated with increased requirement for surgery. CONCLUSION: In this long-term follow-up from a clinical trial, 3-year outcomes remained suboptimal with ongoing poor quality of life and high numbers requiring surgery. Importantly, reduction in CAS in the first year, a commonly used surrogate outcome measure, was not associated with improved long-term outcomes.

Epigenetic drug screen identified IOX1 as an inhibitor of Th17-mediated inflammation through targeting TET2.

BACKGROUND: Targeting helper T cells, especially Th17 cells, has become a plausible therapy for many autoimmune diseases. METHODS: Using an in vitro culture system, we screened an epigenetics compound library for inhibitors of IFN-γ and IL-17 expression in murine Th1 and Th17 cultures. FINDINGS: This identified IOX1 as an effective suppressor of IL-17 expression in both murine and human CD4+ T cells. Furthermore, we found that IOX1 suppresses Il17a expression directly by targeting TET2 activity on its promoter in Th17 cells. Using established pre-clinical models of intraocular inflammation, treatment with IOX1 in vivo reduced the migration/infiltration of Th17 cells into the site of inflammation and tissue damage. INTERPRETATION: These results provide evidence of the strong potential for IOX1 as a viable therapy for inflammatory diseases, in particular of the eye. FUNDING: This study was supported by the National Key Research and Development Program of China 2021YFA1101200 (2021YFA1101204) to LW and XW; the National Natural Science Foundation of China 81900844 to XH and 82171041 to LW; the China Postdoctoral Science Foundation 2021M700776 and the Scientific Research Project of Guangdong Provincial Bureau of Traditional Chinese Medicine 20221373 to YZ; and the National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital NHS (National Health Service) Foundation Trust and University College London Institute of Ophthalmology, UK (DAC, LPS, PJPL, MS, ADD and RWJL). The views expressed are those of the authors and not necessarily those of the NIHR or the UK's Department of Health and Social Care.

A radiomics-based decision support tool improves lung cancer diagnosis in combination with the Herder score in large lung nodules.

BACKGROUND: Large lung nodules (≥15 mm) have the highest risk of malignancy, and may exhibit important differences in phenotypic or clinical characteristics to their smaller counterparts. Existing risk models do not stratify large nodules well. We aimed to develop and validate an integrated segmentation and classification pipeline, incorporating deep-learning and traditional radiomics, to classify large lung nodules according to cancer risk. METHODS: 502 patients from five U.K. centres were recruited to the large-nodule arm of the retrospective LIBRA study between July 2020 and April 2022. 838 CT scans were used for model development, split into training and test sets (70% and 30% respectively). An nnUNet model was trained to automate lung nodule segmentation. A radiomics signature was developed to classify nodules according to malignancy risk. Performance of the radiomics model, termed the large-nodule radiomics predictive vector (LN-RPV), was compared to three radiologists and the Brock and Herder scores. FINDINGS: 499 patients had technically evaluable scans (mean age 69 ± 11, 257 men, 242 women). In the test set of 252 scans, the nnUNet achieved a DICE score of 0.86, and the LN-RPV achieved an AUC of 0.83 (95% CI 0.77-0.88) for malignancy classification. Performance was higher than the median radiologist (AUC 0.75 [95% CI 0.70-0.81], DeLong p = 0.03). LN-RPV was robust to auto-segmentation (ICC 0.94). For baseline solid nodules in the test set (117 patients), LN-RPV had an AUC of 0.87 (95% CI 0.80-0.93) compared to 0.67 (95% CI 0.55-0.76, DeLong p = 0.002) for the Brock score and 0.83 (95% CI 0.75-0.90, DeLong p = 0.4) for the Herder score. In the international external test set (n = 151), LN-RPV maintained an AUC of 0.75 (95% CI 0.63-0.85). 18 out of 22 (82%) malignant nodules in the Herder 10-70% category in the test set were identified as high risk by the decision-support tool, and may have been referred for earlier intervention. INTERPRETATION: The model accurately segments and classifies large lung nodules, and may improve upon existing clinical models. FUNDING: This project represents independent research funded by: 1) Royal Marsden Partners Cancer Alliance, 2) the Royal Marsden Cancer Charity, 3) the National Institute for Health Research (NIHR) Biomedical Research Centre at the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, 4) the National Institute for Health Research (NIHR) Biomedical Research Centre at Imperial College London, 5) Cancer Research UK (C309/A31316).

Gross tumour volume radiomics for prognostication of recurrence & death following radical radiotherapy for NSCLC.

Recurrence occurs in up to 36% of patients treated with curative-intent radiotherapy for NSCLC. Identifying patients at higher risk of recurrence for more intensive surveillance may facilitate the earlier introduction of the next line of treatment. We aimed to use radiotherapy planning CT scans to develop radiomic classification models that predict overall survival (OS), recurrence-free survival (RFS) and recurrence two years post-treatment for risk-stratification. A retrospective multi-centre study of >900 patients receiving curative-intent radiotherapy for stage I-III NSCLC was undertaken. Models using radiomic and/or clinical features were developed, compared with 10-fold cross-validation and an external test set, and benchmarked against TNM-stage. Respective validation and test set AUCs (with 95% confidence intervals) for the radiomic-only models were: (1) OS: 0.712 (0.592-0.832) and 0.685 (0.585-0.784), (2) RFS: 0.825 (0.733-0.916) and 0.750 (0.665-0.835), (3) Recurrence: 0.678 (0.554-0.801) and 0.673 (0.577-0.77). For the combined models: (1) OS: 0.702 (0.583-0.822) and 0.683 (0.586-0.78), (2) RFS: 0.805 (0.707-0.903) and 0·755 (0.672-0.838), (3) Recurrence: 0·637 (0.51-0.·765) and 0·738 (0.649-0.826). Kaplan-Meier analyses demonstrate OS and RFS difference of >300 and >400 days respectively between low and high-risk groups. We have developed validated and externally tested radiomic-based prediction models. Such models could be integrated into the routine radiotherapy workflow, thus informing a personalised surveillance strategy at the point of treatment. Our work lays the foundations for future prospective clinical trials for quantitative personalised risk-stratification for surveillance following curative-intent radiotherapy for NSCLC.

A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models.

BACKGROUND: Surveillance is universally recommended for non-small cell lung cancer (NSCLC) patients treated with curative-intent radiotherapy. High-quality evidence to inform optimal surveillance strategies is lacking. Machine learning demonstrates promise in accurate outcome prediction for a variety of health conditions. The purpose of this study was to utilise readily available patient, tumour, and treatment data to develop, validate and externally test machine learning models for predicting recurrence, recurrence-free survival (RFS) and overall survival (OS) at 2 years from treatment. METHODS: A retrospective, multicentre study of patients receiving curative-intent radiotherapy for NSCLC was undertaken. A total of 657 patients from 5 hospitals were eligible for inclusion. Data pre-processing derived 34 features for predictive modelling. Combinations of 8 feature reduction methods and 10 machine learning classification algorithms were compared, producing risk-stratification models for predicting recurrence, RFS and OS. Models were compared with 10-fold cross validation and an external test set and benchmarked against TNM-stage and performance status. Youden Index was derived from validation set ROC curves to distinguish high and low risk groups and Kaplan-Meier analyses performed. FINDINGS: Median follow-up time was 852 days. Parameters were well matched across training-validation and external test sets: Mean age was 73 and 71 respectively, and recurrence, RFS and OS rates at 2 years were 43% vs 34%, 54% vs 47% and 54% vs 47% respectively. The respective validation and test set AUCs were as follows: 1) RFS: 0·682 (0·575-0·788) and 0·681 (0·597-0·766), 2) Recurrence: 0·687 (0·582-0·793) and 0·722 (0·635-0·81), and 3) OS: 0·759 (0·663-0·855) and 0·717 (0·634-0·8). Our models were superior to TNM stage and performance status in predicting recurrence and OS. INTERPRETATION: This robust and ready to use machine learning method, validated and externally tested, sets the stage for future clinical trials entailing quantitative personalised risk-stratification and surveillance following curative-intent radiotherapy for NSCLC. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

The Role of Artificial Intelligence in Early Cancer Diagnosis.

Improving the proportion of patients diagnosed with early-stage cancer is a key priority of the World Health Organisation. In many tumour groups, screening programmes have led to improvements in survival, but patient selection and risk stratification are key challenges. In addition, there are concerns about limited diagnostic workforces, particularly in light of the COVID-19 pandemic, placing a strain on pathology and radiology services. In this review, we discuss how artificial intelligence algorithms could assist clinicians in (1) screening asymptomatic patients at risk of cancer, (2) investigating and triaging symptomatic patients, and (3) more effectively diagnosing cancer recurrence. We provide an overview of the main artificial intelligence approaches, including historical models such as logistic regression, as well as deep learning and neural networks, and highlight their early diagnosis applications. Many data types are suitable for computational analysis, including electronic healthcare records, diagnostic images, pathology slides and peripheral blood, and we provide examples of how these data can be utilised to diagnose cancer. We also discuss the potential clinical implications for artificial intelligence algorithms, including an overview of models currently used in clinical practice. Finally, we discuss the potential limitations and pitfalls, including ethical concerns, resource demands, data security and reporting standards.

Ibrutinib-related uveitis: A report of two severe cases.

INTRODUCTION: Ibrutinib is a small-molecule drug approved for the treatment of haematological disorders and is known to be associated with visual disturbances, but uveitis has not yet been reported as an adverse effect of this medication. We present two cases of ibrutinib-associated severe uveitis in patients with chronic lymphocytic leukaemia. CASE DESCRIPTION: Our first case is a 65-year-old woman who presented with acute onset of bilateral fibrinous anterior uveitis 1 day after starting ibrutinib. Her vision was hand movements in the right eye and 20/120 in the left with hyperaemic discs and subretinal fluid. Ibrutinib was stopped and she experienced a significant improvement under local and oral steroid treatment. The second case is a 64-year-old male with subacute onset of bilateral hypertensive anterior uveitis with pupillary seclusion and right eye hyphaema. He was on ibrutinib for the past 9 months. His vision at presentation was 20/80 and 20/60 for the right and left eye, respectively. He responded poorly to local steroid treatment until ibrutinib was stopped due to cardiac side-effects, after which his uveitis resolved and treatment was stopped. CONCLUSION: The temporal association between changes in ibrutinib treatment and our patients' ocular inflammation suggests a causative link. Ibrutinib increases Th1-based immune responses which is proposed as a mechanism for drug-induced uveitis. Its antiplatelet effect may explain the fibrinous nature of the inflammation and hyphaema.

The Effect of Ophthalmic Surgery for Graves' Orbitopathy on Quality of Life: A Systematic Review and Meta-Analysis.

Background: Graves' orbitopathy (GO) has a profound negative impact on quality of life. Surgery is undertaken to preserve vision, correct diplopia, and improve aesthetics. We sought to quantify the effect of different surgical approaches on quality of life. Methods: Electronic databases Ovid-MEDLINE and EMBASE were used from inception until March 22, 2021, to identify studies assessing quality of life pre- and postsurgical intervention for GO. Two reviewers independently extracted data and performed quality assessments. Random-effects and Bayesian models for meta-analyses were utilized. Results: Ten articles comprising 632 patients with a mean age of 48.4 years (range 16-85 years) were included. All used the Graves' Ophthalmopathy Quality of Life (GO-QOL) questionnaire. For GO-QOL appearance, the pooled standardized mean improvement for patients after surgery was +0.72 (95% confidence interval [CI 0.50-0.94]), I2 = 69% [CI 52-80%]. For GO-QOL visual functioning, the pooled standardized mean difference (SMD) for patients after surgery was +0.41 [CI 0.25-0.58], I2 = 60% [CI 36-74%]. For visual appearance, orbital decompression yielded the greatest improvement (SMD +0.84 [CI 0.54-1.13]) followed by eyelid surgery (SMD +0.38 [CI 0.05-0.70]), while strabismus correction had no significant effect (SMD +0.94 [CI -0.10 to 1.99]). Conversely strabismus correction was associated with the greatest improvement (SMD +1.25 [CI 0.29-2.21]) in visual functioning, outperforming orbital decompression (SMD +0.29 [CI 0.15-0.43]) and eyelid surgery (SMD +0.12 [CI -0.18 to 0.41]). A mean improvement in GO-QOL of greater than 10 points after orbital decompression surgery was achieved in 12/14 (86%) patient groups for appearance and 5/14 (36%) patient groups for visual functioning. A mean improvement of greater than 6 points was achieved in 5 of 6 (83%) patient groups for strabismus surgery for both appearance and visual functioning. A mean improvement of greater than 6 points after eyelid surgery was achieved in 2/3 (67%) patient groups and 0/3 patient groups for visual appearance and functioning, respectively. Conclusion: Ophthalmic surgery results in substantial improvements in quality of life in patients with GO, with greater perceived effects on appearance than visual function. Orbital decompression has particular impact on visual appearance; strabismus surgery may benefit both visual appearance and function equally, whereas eyelid surgery benefits appearance alone.

Effect of Weight Loss and Continuous Positive Airway Pressure on Obstructive Sleep Apnea and Metabolic Profile Stratified by Craniofacial Phenotype: A Randomized Clinical Trial.

Rationale: Craniofacial structure is believed to modulate the effect of weight loss on obstructive sleep apnea (OSA), but whether this affects metabolic profile after weight loss compared with continuous positive airway pressure (CPAP) is unknown among obese Chinese patients with OSA. Objectives: To compare the change in metabolic profile between a lifestyle modification program (LMP), stratified by craniofacial phenotype, and CPAP therapy for 6 months. Methods: We randomly assigned 194 patients with body mass index ⩾ 25 kg/m2 and moderate to severe OSA to participate in the LMP or receive CPAP therapy for 6 months in a 2:1 ratio. Assessments included computed tomography for assessing maxillomandibular volume (MMV), hsCRP (high-sensitivity C-reactive protein), and insulin sensitivity. Measurements and Main Results: Among 128 and 66 subjects in the LMP and CPAP groups, respectively, hsCRP was reduced more in the LMP group than the CPAP group (median [interquartile range], -0.7 [-1.4 to -0.0] vs. -0.3 [-0.9 to 0.4] mg/L; P = 0.012). More patients in the LMP group achieved low hsCRP (<1 mg/L) than the CPAP group (21.1% vs. 9.1%; P = 0.04). Insulin sensitivity improved only in the LMP group, with 3.1 (95% confidence interval, 1.5-6.6) times more patients with normal glucose regulation after intervention. The LMP group was stratified into LMP-small MMV (n = 64) and LMP-large MMV (n = 64) groups according to the median MMV value of 233.2 cm3. There was no significant difference in hsCRP (median [interquartile range], -0.7 [-1.3 to 0.1] vs. -0.7 [-1.5 to -0.2] mg/L; P = 0.884) and insulin sensitivity (median [interquartile range], 0.5 [-0.2 to 1.9] vs. 0.6 [0.1 to 2.0]; P = 0.4860) between the LMP-small MMV and LMP-large MMV groups. Conclusions: Weight reduction alleviated subclinical inflammation and improved insulin sensitivity more than CPAP among obese Chinese patients with moderate to severe OSA, and this effect was not influenced by craniofacial structure. Clinical trial registered with www.clinicaltrials.gov (NCT03287973).