RESUMO
Obstructive sleep apnea (OSA) is a global health concern and is typically diagnosed using in-laboratory polysomnography (PSG). However, PSG is highly time-consuming and labor-intensive. We, therefore, developed machine learning models based on easily accessed anthropometric features to screen for the risk of moderate to severe and severe OSA. We enrolled 3503 patients from Taiwan and determined their PSG parameters and anthropometric features. Subsequently, we compared the mean values among patients with different OSA severity and considered correlations among all participants. We developed models based on the following machine learning approaches: logistic regression, k-nearest neighbors, naïve Bayes, random forest (RF), support vector machine, and XGBoost. Collected data were first independently split into two data sets (training and validation: 80%; testing: 20%). Thereafter, we adopted the model with the highest accuracy in the training and validation stage to predict the testing set. We explored the importance of each feature in the OSA risk screening by calculating the Shapley values of each input variable. The RF model achieved the highest accuracy for moderate to severe (84.74%) and severe (72.61%) OSA. The level of visceral fat was found to be a predominant feature in the risk screening models of OSA with the aforementioned levels of severity. Our machine learning models can be employed to screen for OSA risk in the populations in Taiwan and in those with similar craniofacial structures.
Assuntos
Apneia Obstrutiva do Sono , Humanos , Teorema de Bayes , Apneia Obstrutiva do Sono/diagnóstico , Polissonografia , Antropometria , Aprendizado de MáquinaRESUMO
BACKGROUND AND PURPOSE: Chemoradiotherapy (CRT) for locally-advanced non-small cell lung cancer (LA-NSCLC) has undergone advances, including increased overall survival (OS) when combined with immune checkpoint blockade (ICB), and using cardiac-sparing techniques to reduce the radiotoxicity. This research investigated 1) how radiotherapy schedules can be optimised with CRT-ICB schemes, and 2) how cardiac-sparing might change the OS for concurrent CRT (cCRT). METHODS AND MATERIALS: Survival data and dosimetric indices were sourced from published studies, with 2-year OS standardised and the hazard ratio of mean heart dose (MHD) against radiotoxicity tabulated in purpose. A published CRT dose-response model was selected, then modified with ICB and cardiac-sparing hypotheses. Models were maximum likelihood fitted, then visualised the prediction outcomes after bootstrapping. RESULTS: The modelled 2-year OS rate of cCRT-ICB reached 71â¯% (95â¯% confidence intervals, CI 62â¯%, 84â¯%) and 66â¯% (95â¯% CI: 53â¯%, 81â¯%) for stage IIIA and IIIB/C, respectively, given 60â¯Gy in 2â¯Gy-per-fraction. 60â¯Gy in 30 fractions remained the best schedule for cCRT-ICB, whereas modest dose de-escalation to 55â¯Gy only reduced the OS in 2â¯%. Sequential CRT (sCRT)-ICB provided 6â¯% OS increases versus the best OS rate achieved by sCRT alone. Photon MHD-sparing achieved a 5-10â¯% increase in modelled 2-year OS, with protons providing a further roughly 5-10â¯% increase. CONCLUSION: Neither dose-escalation nor de-escalation relative to 60â¯Gy in 30 fractions influenced the survival with cCRT-ICB, while 5â¯Gy dose de-escalation might benefit patients with heavily irradiated organs at risk. Cardiac-sparing improved OS, and protons provided advantages for tumours anatomically overlapped or lay below the heart.
RESUMO
PURPOSE: Adding immune checkpoint blockade (ICB) to concurrent chemoradiotherapy (cCRT) has improved overall survival (OS) for inoperable locally advanced non-small cell lung cancer. Trials of cCRT-ICB are heterogeneous for factors such as tumor stage and histology, programmed cell death ligand-1 (PDL-1) status, and cCRT-ICB schedules. We therefore aimed to determine the ICB contribution to survival across studies and identify factors associated with survival gain. METHODS AND MATERIALS: Data were collated from cCRT-ICB clinical studies published 2018 to 2022 that treated 2196 patients with non-small cell lung cancer (99% stage 3). Associations between 2-year OS and ICB, CRT, patient and tumor factors were investigated using metaregression. A published model of survival after radiation therapy (RT) or CRT was extended to include ICB effects. The model was fitted simultaneously to the cCRT-ICB data and data previously compiled for RT/CRT treatments alone. The net ICB contribution (OS gain) and its associations with factors were described by fitted values of ICB terms added to the model. Statistical significance was determined by likelihood-ratio testing. RESULTS: The gain in 2-year OS from ICB was 9.9% overall (95% CI, 7.6%, 12.2%; P = .018). Both OS gain and 2-year OS itself rose with increasing planned ICB duration (P = .008, .002, respectively) and with tumor PDL-1 ≥ 1% (P = .034, .023). Fitted OS gains were also greater for patients with stage 3B/C disease (P = .021). OS gain was not associated with tumor histology, patient performance status, radiation therapy dose, ICB drug type (anti-PDL-1 vs anti-programmed cell death-1), or whether ICB began concurrently with or after cCRT. CONCLUSIONS: Fitted gains in 2-year OS due to ICB were higher in cohorts with greater fractions of stage 3B/C patients and patients with tumor PDL-1 ≥ 1%. OS gain was also significantly higher in a single cohort with a planned ICB duration of 2 years rather than 1, but was not associated with whether ICB treatment began during versus after CRT.
RESUMO
Background: Exposure to air pollution may be a risk factor for obstructive sleep apnea (OSA) because air pollution may alter body water distribution and aggravate OSA manifestations. Objectives: This study aimed to investigate the mediating effects of air pollution on the exacerbation of OSA severity through body water distribution. Methods: This retrospective study analyzed body composition and polysomnographic data collected from a sleep center in Northern Taiwan. Air pollution exposure was estimated using an adjusted nearest method, registered residential addresses, and data from the databases of government air quality motioning stations. Next, regression models were employed to determine the associations between estimated air pollution exposure levels (exposure for 1, 3, 6, and 12 months), OSA manifestations (sleep-disordered breathing indices and respiratory event duration), and body fluid parameters (total body water and body water distribution). The association between air pollution and OSA risk was determined. Results: Significant associations between OSA manifestations and short-term (1 month) exposure to PM2.5 and PM10 were identified. Similarly, significant associations were identified among total body water and body water distribution (intracellular-to-extracellular body water distribution), short-term (1 month) exposure to PM2.5 and PM10, and medium-term (3 months) exposure to PM10. Body water distribution might be a mediator that aggravates OSA manifestations, and short-term exposure to PM2.5 and PM10 may be a risk factor for OSA. Conclusion: Because exposure to PM2.5 and PM10 may be a risk factor for OSA that exacerbates OSA manifestations and exposure to particulate pollutants may affect OSA manifestations or alter body water distribution to affect OSA manifestations, mitigating exposure to particulate pollutants may improve OSA manifestations and reduce the risk of OSA. Furthermore, this study elucidated the potential mechanisms underlying the relationship between air pollution, body fluid parameters, and OSA severity.
Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Ambientais , Apneia Obstrutiva do Sono , Humanos , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Exposição Ambiental/efeitos adversos , Material Particulado/efeitos adversos , Material Particulado/análise , Estudos Retrospectivos , Apneia Obstrutiva do Sono/epidemiologia , Água CorporalRESUMO
BACKGROUND: Air pollution may alter body water distribution, it may also be linked to low-arousal-threshold obstructive sleep apnoea (low-ArTH OSA). Here, we explored the mediation effects of air pollution on body water distribution and low-ArTH OSA manifestations. METHODS: In this retrospective study, we obtained sleep centre data from healthy participants and patients with low-ArTH OSA (N=1924) in northern Taiwan. Air pollutant exposure at different time intervals (1, 3, 6 and 12 months) was estimated using the nearest station estimation method, and government air-quality data were also obtained. Regression models were used to assess the associations of estimated exposure, sleep disorder indices and body water distribution with the risk of low-ArTH OSA. Mediation analysis was performed to explore the relationships between air pollution, body water distribution and sleep disorder indices. RESULTS: First, exposure to particulate matter (PM) with a diameter of ≤10 µm (PM10) for 1 and 3 months and exposure to PM with a diameter of ≤2.5 µm (PM2.5) for 3 months were significantly associated with the Apnoea-Hypopnoea Index (AHI), Oxygen Desaturation Index (ODI), Arousal Index (ArI) and intracellular-to-extracellular water ratio (I-E water ratio). Significant associations were observed between the risk of low-ArTH OSA and 1- month exposure to PM10 (OR 1.42, 95% CI 1.09 to 1.84), PM2.5 (OR 1.33, 95% CI 1.02 to 1.74) and ozone (OR 1.27, 95% CI 1.01 to 1.6). I-E water ratio alternation caused by 1-month exposure to PM10 and 3-month exposure to PM2.5 and PM10 had partial mediation effects on AHI and ODI. CONCLUSION: Air pollution can directly increase sleep disorder indices (AHI, ODI and ArI) and alter body water distribution, thus mediating the risk of low-ArTH OSA.
Assuntos
Poluentes Atmosféricos , Apneia Obstrutiva do Sono , Humanos , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Estudos Retrospectivos , Água Corporal/química , Apneia Obstrutiva do Sono/epidemiologia , Material Particulado/efeitos adversos , Material Particulado/análise , Oxigênio , Nível de Alerta , ÁguaRESUMO
Obstructive sleep apnea (OSA) is a risk factor for neurodegenerative diseases. This study determined whether continuous positive airway pressure (CPAP), which can alleviate OSA symptoms, can reduce neurochemical biomarker levels. Thirty patients with OSA and normal cognitive function were recruited and divided into the control (n = 10) and CPAP (n = 20) groups. Next, we examined their in-lab sleep data (polysomnography and CPAP titration), sleep-related questionnaire outcomes, and neurochemical biomarker levels at baseline and the 3-month follow-up. The paired t-test and Wilcoxon signed-rank test were used to examine changes. Analysis of covariance (ANCOVA) was performed to increase the robustness of outcomes. The Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index scores were significantly decreased in the CPAP group. The mean levels of total tau (T-Tau), amyloid-beta-42 (Aß42), and the product of the two (Aß42 × T-Tau) increased considerably in the control group (ΔT-Tau: 2.31 pg/mL; ΔAß42: 0.58 pg/mL; ΔAß42 × T-Tau: 48.73 pg2/mL2), whereas the mean levels of T-Tau and the product of T-Tau and Aß42 decreased considerably in the CPAP group (ΔT-Tau: -2.22 pg/mL; ΔAß42 × T-Tau: -44.35 pg2/mL2). The results of ANCOVA with adjustment for age, sex, body mass index, baseline measurements, and apnea-hypopnea index demonstrated significant differences in neurochemical biomarker levels between the CPAP and control groups. The findings indicate that CPAP may reduce neurochemical biomarker levels by alleviating OSA symptoms.
RESUMO
(1) Purpose: We analysed overall survival (OS) rates following radiotherapy (RT) and chemo-RT of locally-advanced non-small cell lung cancer (LA-NSCLC) to investigate whether tumour repopulation varies with treatment-type, and to further characterise the low α/ß ratio found in a previous study. (2) Materials and methods: Our dataset comprised 2-year OS rates for 4866 NSCLC patients (90.5% stage IIIA/B) belonging to 51 cohorts treated with definitive RT, sequential chemo-RT (sCRT) or concurrent chemo-RT (cCRT) given in doses-per-fraction ≤3 Gy over 16-60 days. Progressively more detailed dose-response models were fitted, beginning with a probit model, adding chemotherapy effects and survival-limiting toxicity, and allowing tumour repopulation and α/ß to vary with treatment-type and stage. Models were fitted using the maximum-likelihood technique, then assessed via the Akaike information criterion and cross-validation. (3) Results: The most detailed model performed best, with repopulation offsetting 1.47 Gy/day (95% confidence interval, CI: 0.36, 2.57 Gy/day) for cCRT but only 0.30 Gy/day (95% CI: 0.18, 0.47 Gy/day) for RT/sCRT. The overall fitted tumour α/ß ratio was 3.0 Gy (95% CI: 1.6, 5.6 Gy). (4) Conclusion: The fitted repopulation rates indicate that cCRT schedule durations should be shortened to the minimum in which prescribed doses can be tolerated. The low α/ß ratio suggests hypofractionation should be efficacious.