Tag: statistics

BMC Cancer. 2022 Oct 1;22(1):1031. doi: 10.1186/s12885-022-10125-1.

ABSTRACT

BACKGROUND: Both Response Evaluation Criteria in Solid Tumors (RECIST) and tumor regression grade (TRG) play key roles in evaluating tumor response. We analyzed the consistency of TRG and RECIST 1.1 for gastric cancer (GC) patients and compared their prognostic values.

METHODS: Patients with GC who received preoperative chemotherapy or chemoimmunotherapy and had records of TRG from December 2013 to October 2021 were enrolled retrospectively. TRG 0-1 and 2-3 are considered as corresponding to complete response (CR)/partial response (PR) and stable disease (SD)/progress disease (PD) in RECIST 1.1, respectively. The primary endpoints were disease-free survival (DFS) and overall survival (OS). The consistency of RECIST and TRG was examined by kappa statistics. Survival analysis was performed using the Kaplan Meier method.

RESULT: One hundred fifty seven GC patients were enrolled, including 125 with preoperative chemotherapy and 32 with chemoimmunotherapy. Among them, 56 patients had measurable lesions. Only 19.6% (11/56) of the patients had consistent results between RECIST 1.1 and TRG. TRG was correlated with both OS and DFS (P = 0.02 and 0.03, respectively) while response according to RECIST1.1 was not (P = 0.86 and 0.23, respectively). The median DFS had not reached in the TRG 0-1 group and was 16.13 months in TRG 2-3 group. TRG 2-3 was associated with young age and peritoneal or liver metastasis. Besides, preoperative chemoimmunotherapy had a significantly higher pCR rate than chemotherapy alone (34.4% vs 8.0%, P < 0.001).

CONCLUSION: TRG was in poor agreement with RECIST 1.1. TRG was better than RECIST 1.1 in predicting DFS and OS for GC patients who received preoperative therapy.

PMID:36183074 | DOI:10.1186/s12885-022-10125-1

BMC Med Res Methodol. 2022 Oct 1;22(1):258. doi: 10.1186/s12874-022-01741-3.

ABSTRACT

BACKGROUND: Current dose-finding designs for phase I clinical trials can correctly select the MTD in a range of 30-80% depending on various conditions based on a sample of 30 subjects. However, there is still an unmet need for efficiency and cost saving.

METHODS: We propose a novel dose-finding design based on Bayesian stochastic approximation. The design features utilization of dose level information through local adaptive modelling and free assumption of toxicity probabilities and hyper-parameters. It allows a flexible target toxicity rate and varying cohort size. And we extend it to accommodate historical information via prior effective sample size. We compare the proposed design to some commonly used methods in terms of accuracy and safety by simulation.

RESULTS: On average, our design can improve the percentage of correct selection to about 60% when the MTD resides at a early or middle position in the search domain and perform comparably to other competitive methods otherwise. A free online software package is provided to facilitate the application, where a simple decision tree for the design can be pre-printed beforehand.

CONCLUSION: The paper proposes a novel dose-finding design for phase I clinical trials. Applying the design to future cancer trials can greatly improve the efficiency, consequently save cost and shorten the development period.

PMID:36183071 | DOI:10.1186/s12874-022-01741-3

BMC Womens Health. 2022 Oct 1;22(1):397. doi: 10.1186/s12905-022-01907-7.

ABSTRACT

BACKGROUND: Domestic violence (DV) against women is a global issue that affects women in all countries and is a significant contributor to their poor health. Women who have experienced DV, in particular, suffer from the gynecological, nervous system, and stress-related issues. Despite such devastating implications, there is a paucity of data on the prevalence of DV and its associated factors among married reproductive-age women in Cameroon.

METHOD: The data were analyzed by using STATA version 14 from a demographic and health survey conducted in Cameroon in 2018. Both bivariable and multivariable logistic regression analyses were done. Statistical significance was determined using a p-value of less than 0.05 and a 95% confidence range.

RESULT: A total of 4,903 ever-married women were included in the study. The mean age ± standard deviation, of the participants was 31.3 (± 8.4) years with an age range of 15-49 years. The prevalence of DV among ever-married Cameroonian women was 30.5% with 95%CI (29.3%, 31.8%). Women’s educational attainment (higher educational level) (AOR = 0.58, 95% CI (0.37, 0.92), p value = 0.02), Husband’s educational level (husbands who attended primary educational level (AOR = 1.30, 95% CI (1.01, 1.68), p value = 0.04), a woman who had media exposure regarding DV ( AOR = 0.83, 95% CI (0.0, 0.99), p value = 0.04), a woman whose husband drinks alcohol (AOR = 3.00, 95% CI (2.56, 3.53), p value < 0.001), and the region where the women reside (center without Yaoundé (AOR = 2.48, 95% CI (1.75, 3.52), p value < 0.001), west (AOR = 1.49, 95% CI (1.05, 2.11), p value = 0.02), South (AOR = 1.89, 95% CI (1.31, 2.72), p-value = 0.001), and Yaoundé (AOR = 1.65. 95% CI (1.14, 2.39), p value = 0.009) were factors that were significantly associated to DV committed by a husband in the previous 12 months against ever-married women.

CONCLUSION: The present study revealed that the prevalence of DV among ever-married women in Cameroon is high. Women’s educational level, husband’s educational level, husband’s alcohol drinking status, women’s exposure to mass-media about DV, and the region where the woman resides in the country were factors significantly associated with DV.

PMID:36183059 | DOI:10.1186/s12905-022-01907-7

BMC Public Health. 2022 Oct 1;22(1):1841. doi: 10.1186/s12889-022-14242-1.

ABSTRACT

The infant mortality rate (IMR) is still a key indicator in a middle-income country such as Ecuador where a slightly increase up to 11.75 deaths per thousand life births has been observed in 2019. The purpose of this study is to propose and apply a prioritization method that combines clusters detection (Local Indicators of Spatial Association, LISA) and a monotonic statistic depicting time trend over 10 years (Mann-Kendall) at municipal level. Annual national databases (2010 to 2019) of live births and general deaths are downloaded from National Institute of Statistics and Censuses (INEC). The results allow identifying a slight increase in the IMR at the national level from 9.85‰ in 2014 to 11.75‰ in 2019, neonatal mortality accounted for 60% of the IMR in the last year. The LISA analysis allowed observing that the high-high clusters are mainly concentrated in the central highlands. At the local level, Piñas, Cuenca, Ibarra and Babahoyo registered the highest growth trends (0.7,1). The combination of techniques made it possible to identify eight priority counties, half of them pertaining to the highlands region, two to the coastal region and two to the Amazon region. To keep infant mortality at a low level is necessary to prioritize critical areas where public allocation of funds should be concentrated and formulation of policies.

PMID:36183054 | DOI:10.1186/s12889-022-14242-1

Sci Rep. 2022 Oct 1;12(1):16471. doi: 10.1038/s41598-022-20522-y.

ABSTRACT

A prospective randomized control trial of 140 eyes from 140 patients, who underwent phacoemulsification, was conducted to compare the efficacy of subtenon corticosteroids injection with corticosteroids eye drops for controlling postoperative intraocular inflammation. Seventy patients received subtenon 20-mg triamcinolone injection (TA group), whereas the other 70 patients received 0.1% dexamethasone eye drops (Dexa group) after the uneventful surgeries. We examined and measured anterior chamber inflammation (ACI) score, laser flare-cell metering, conjunctival redness, pain, discomfort, visual acuity, intraocular pressure, and central foveal thickness on 1, 7, 14, 28 and 90 days postoperatively. At one month after the surgery, full recovery (zero ACI score) was found in 43 patients (63.20%) in the Dexa group versus 47 patients (68.10%) in the TA group (p = 0.55). There were no statistically significant differences in aqueous cells (p = 0.37) and flare (p = 0.86) between the two groups at one month. All participants experienced no serious adverse events. In conclusion, we found no statistically significant difference between subtenon 20-mg triamcinolone injection and 0.1% dexamethasone eye drop to control inflammation postoperatively. A single subtenon 20-mg triamcinolone injection could be an alternative anti-inflammatory treatment for an uneventful phacoemulsification.

PMID:36183042 | DOI:10.1038/s41598-022-20522-y

Psychometrika. 2022 Oct 1. doi: 10.1007/s11336-022-09887-1. Online ahead of print.

ABSTRACT

Latent class models are powerful statistical modeling tools widely used in psychological, behavioral, and social sciences. In the modern era of data science, researchers often have access to response data collected from large-scale surveys or assessments, featuring many items (large J) and many subjects (large N). This is in contrary to the traditional regime with fixed J and large N. To analyze such large-scale data, it is important to develop methods that are both computationally efficient and theoretically valid. In terms of computation, the conventional EM algorithm for latent class models tends to have a slow algorithmic convergence rate for large-scale data and may converge to some local optima instead of the maximum likelihood estimator (MLE). Motivated by this, we introduce the tensor decomposition perspective into latent class analysis with binary responses. Methodologically, we propose to use a moment-based tensor power method in the first step and then use the obtained estimates as initialization for the EM algorithm in the second step. Theoretically, we establish the clustering consistency of the MLE in assigning subjects into latent classes when N and J both go to infinity. Simulation studies suggest that the proposed tensor-EM pipeline enjoys both good accuracy and computational efficiency for large-scale data with binary responses. We also apply the proposed method to an educational assessment dataset as an illustration.

PMID:36183034 | DOI:10.1007/s11336-022-09887-1

Eur Arch Otorhinolaryngol. 2022 Oct 1. doi: 10.1007/s00405-022-07668-1. Online ahead of print.

ABSTRACT

BACKGROUND: To create nomograms for better prediction of the oncological outcome in advanced laryngeal (LxCAs) or hypopharyngeal (HpxCAs) cancer after laryngopharyngectomy.

MATERIALS: 239 patients who underwent total laryngectomy or laryngopharyngectomy due to LxCA (52.7%) or HpxCA (47.3%) were included in this study. Based on clinical risk factors (tumor site, lymph node involvement, salvage setting), we created nomograms for prediction of disease-specific survival (DSS) and disease-free survival (DFS).

RESULTS: HpxCAs showed a higher rate of lymph node involvement (p < 0.001), a 2.47-fold higher risk of a 2nd head and neck cancer (p = 0.009) and significantly worse loco-regional control rates (p = 0.003) compared to LxCAs. Positive neck nodes and salvage procedures were associated with significantly worse outcome. Nomograms demonstrated that hypopharyngeal tumors with positive neck nodes in salvage situations had the worst oncological outcome with a 5-year DSS of 15-20%.

CONCLUSIONS: The oncological outcome is worse in hypopharyngeal carcinomas and could be easily quantified by our nomograms that are based on tumor site, lymph node involvement and salvage situation.

PMID:36183023 | DOI:10.1007/s00405-022-07668-1

Sci Rep. 2022 Oct 1;12(1):16475. doi: 10.1038/s41598-022-20872-7.

ABSTRACT

Tuberculosis is the most common opportunistic infection among HIV/AIDS patients, including those following Antiretroviral Therapy treatment. The risk of tuberculosis infection is higher in people living with HIV/AIDS than in people who are free from HIV/AIDS. Many studies focused on prevalence and determinants of tuberculosis in HIV/AIDS patients without taking into account the censoring aspects of the time to event data. Therefore, this study was undertaken with aim to model time to tuberculosis co-infection of HIV/AIDS patients under follow-up at Jimma Medical Center, Ethiopia using Bayesian parametric survival models. A data of a retrospective cohort of 421 HIV/AIDS patients under follow-up from January 2016 to December 2020 until active tuberculosis was diagnosed or until the end of the study was collected from Jimma Medical Center, Ethiopia. The analysis of the data was performed using R-INLA software package. In order to identify the risk factors which have association with tuberculosis co-infection survival time, Bayesian parametric accelerated failure time survival models were fitted to the data using Integrated Nested Laplace Approximation methodology. About 26.37% of the study subjects had been co-infected with tuberculosis during the study period. Among the parametric accelerated failure time models, the Bayesian log-logistic accelerated failure time model was found to be the best fitting model for the data. Patients who lived in urban areas had shorter tuberculosis co-infection free survival time compared to those who lived in rural areas with an acceleration factor of 0.2842. Patients who smoke and drink alcohol had also shorter tuberculosis co-infection survival time than those who do not smoke and drink alcohol respectively. Patients with advanced WHO clinical stages(Stage III and IV), bedridden functional status, low body mass index and severe anemic status had shorter tuberculosis co-infection survival time. Place of residence, smoking, drinking alcohol, larger family size, advanced clinical stages(Stage III and Stage IV), bedridden functional status, CD4 count ([Formula: see text] 200 cells/mm³ and 200-349 cells/mm³), low body mass index and low hemoglobin are the factors that lead to shorter tuberculosis co-infection survival time in HIV/AIDS patients. The findings of the study suggested us to forward the recommendations to modify patients’ life style, early screening and treatment of opportunistic diseases like anemia , as well as effective treatment and management of tuberculosis and HIV co-infection are important to prevent tuberculosis and HIV co-infection.

PMID:36182998 | DOI:10.1038/s41598-022-20872-7

EJNMMI Phys. 2022 Oct 1;9(1):68. doi: 10.1186/s40658-022-00496-6.

ABSTRACT

BACKGROUND: Performance assessment of positron emission tomography (PET) scanners is crucial to guide clinical practice with efficiency. Even though clinical data are the final target, their use to characterize systems response is constrained by the lack of ground truth. Phantom tests overcome this limitation by controlling the object of study, but remain simple and are not representative of patient complexity. The objective of this study is to evaluate the accuracy of a simulation method using synthetic spheres inserted into acquired raw data prior to reconstruction, simulating multiple scenarios in comparison with equivalent physical experiments.

METHODS: We defined our experimental framework using the National Electrical Manufacturers Association NU-2 2018 Image Quality standard, but replaced the standard sphere set with more appropriate sizes (4, 5, 6, 8, 10 and 13 mm) better suited to current PET scanner performance. Four experiments, with different spheres-to-background ratios (2:1, 4:1, 6:1 and 8:1), were performed. An additional dataset was acquired with a radioactive background but no activity within the spheres (water only) to establish a baseline. Then, we artificially simulated radioactive spheres to reproduce other experiments using synthetic data inserted into the original sinogram. Images were reconstructed following standard guidelines using ordered subset expectation maximization algorithm along with a Bayesian penalized likelihood algorithm. We first visually compared experimental and simulated images. Afterward, we measured the activity concentration values into the spheres to calculate the mean and maximum recovery coefficients (RC_mean and RC_max) which we used in a quantitative analysis.

RESULTS: No significant visual differences were identified between experimental and simulated series. Mann-Whitney U tests comparing simulated and experimental distributions showed no statistical differences for both RC_mean (P value = 0.611) and RC_max (P value = 0.720). Spearman tests revealed high correlation for RC_mean (ρ = 0.974, P value < 0.001) and RC_max (ρ = 0.974, P value < 0.001) between both datasets. From Bland-Altman plots, we highlighted slight shifts in RC_mean and RC_max of, respectively, 2.1 ± 16.9% and 3.3 ± 22.3%.

CONCLUSIONS: We evaluated the efficiency of our hybrid method in faithfully mimicking practical situations producing satisfactory results compared to equivalent experimental data.

PMID:36182994 | DOI:10.1186/s40658-022-00496-6

Cell Death Differ. 2022 Oct 1. doi: 10.1038/s41418-022-01069-x. Online ahead of print.

ABSTRACT

Radiation exposure of healthy cells can halt cell cycle temporarily or permanently. In this work, we analyze the time evolution of p21 and p53 from two single cell datasets of retinal pigment epithelial cells exposed to several levels of radiation, and in particular, the effect of radiation on cell cycle arrest. Employing various quantification methods from signal processing, we show how p21 levels, and to a lesser extent p53 levels, dictate whether the cells are arrested in their cell cycle and how frequently these mitosis events are likely to occur. We observed that single cells exposed to the same dose of DNA damage exhibit heterogeneity in cellular outcomes and that the frequency of cell division is a more accurate monitor of cell damage rather than just radiation level. Finally, we show how heterogeneity in DNA damage signaling is manifested early in the response to radiation exposure level and has potential to predict long-term fate.

PMID:36182991 | DOI:10.1038/s41418-022-01069-x