Nevin Manimala

Behav Res Methods. 2023 Mar 3. doi: 10.3758/s13428-023-02072-x. Online ahead of print.

ABSTRACT

Statistical methods generally have assumptions (e.g., normality in linear regression models). Violations of these assumptions can cause various issues, like statistical errors and biased estimates, whose impact can range from inconsequential to critical. Accordingly, it is important to check these assumptions, but this is often done in a flawed way. Here, I first present a prevalent but problematic approach to diagnostics-testing assumptions using null hypothesis significance tests (e.g., the Shapiro-Wilk test of normality). Then, I consolidate and illustrate the issues with this approach, primarily using simulations. These issues include statistical errors (i.e., false positives, especially with large samples, and false negatives, especially with small samples), false binarity, limited descriptiveness, misinterpretation (e.g., of p-value as an effect size), and potential testing failure due to unmet test assumptions. Finally, I synthesize the implications of these issues for statistical diagnostics, and provide practical recommendations for improving such diagnostics. Key recommendations include maintaining awareness of the issues with assumption tests (while recognizing they can be useful), using appropriate combinations of diagnostic methods (including visualization and effect sizes) while recognizing their limitations, and distinguishing between testing and checking assumptions. Additional recommendations include judging assumption violations as a complex spectrum (rather than a simplistic binary), using programmatic tools that increase replicability and decrease researcher degrees of freedom, and sharing the material and rationale involved in the diagnostics.

PMID:36869217 | DOI:10.3758/s13428-023-02072-x

ANZ J Surg. 2023 Mar 3. doi: 10.1111/ans.18356. Online ahead of print.

ABSTRACT

BACKGROUND: To determine surgical, survival and quality of life outcomes across different tumour streams and lessons learned over 28 years.

METHODS: Consecutive patients undergoing pelvic exenteration at a single, high volume, referral hospital, between 1994 and 2022 were included. Patients were grouped according to their tumour type at presentation as follows, advanced primary rectal cancer, other advanced primary malignancy, locally recurrent rectal cancer, other locally recurrent malignancy and non-malignant indications. The main outcomes included, resection margins, postoperative morbidity, long-term overall survival, and quality of life outcomes. Non-parametric statistics and survival analyses were performed to compare outcomes between groups.

RESULTS: Of the 1023 pelvic exenterations performed, 981 (95.9%) unique patients were included. Most patients underwent pelvic exenteration due to locally recurrent rectal cancer (N = 321, 32.7%) or advanced primary rectal cancer (N = 286, 29.2%). The rates of clear surgical margins (89.2%; P < 0.001) and 30-days mortality were higher in the advanced primary rectal cancer group (3.2%; P = 0.025). The 5-year overall survival rates were 66.3% in advanced primary rectal cancer and 44.6% in locally recurrent rectal cancer. Quality of life outcomes differed across groups at baseline, but generally had good trajectories thereafter. International benchmarking revelled excellent comparative outcomes.

CONCLUSIONS: The results of this study demonstrate excellent outcomes overall, but significant differences in surgical, survival and quality of life outcomes across patients undergoing pelvic exenteration due to different tumour streams. The data reported in this manuscript can be utilized by other centres as benchmarking as well as proving both subjective and objective outcome details to support informed decision-making for patients.

PMID:36869215 | DOI:10.1111/ans.18356

Sci Rep. 2023 Mar 3;13(1):3612. doi: 10.1038/s41598-023-30859-7.

ABSTRACT

A growing body of research has shown how important vitamin D is in the prognosis of coronavirus disease 19 (COVID-19). The vitamin D receptor is necessary for vitamin D to perform its effects, and its polymorphisms can help in this regard. Therefore, we aimed to evaluate whether the association of ApaI rs7975232 and BsmI rs1544410 polymorphisms in different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants were influential in the outcomes of COVID-19. The polymerase chain reaction-restriction fragment length polymorphism method was utilized to determine the different genotypes of ApaI rs7975232 and BsmI rs1544410 in 1734 and 1450 patients who had recovered and deceased, respectively. Our finding revealed that the ApaI rs7975232 AA genotype in the Delta and Omicron BA.5 and the CA genotype in the Delta and Alpha variants were associated with higher mortality rate. Also, the BsmI rs1544410 GG genotype in the Delta and Omicron BA.5 and the GA genotype in the Delta and Alpha variants were related to a higher mortality rate. The A-G haplotype was linked with COVID-19 mortality in both the Alpha and Delta variants. The A-A haplotype for the Omicron BA.5 variants was statistically significant. In conclusion, our research revealed a connection between SARS-CoV-2 variants and the impacts of ApaI rs7975232 and BsmI rs1544410 polymorphisms. However, more research is still needed to substantiate our findings.

PMID:36869206 | DOI:10.1038/s41598-023-30859-7

Ther Innov Regul Sci. 2023 Mar 3. doi: 10.1007/s43441-022-00495-w. Online ahead of print.

ABSTRACT

The use of Bayesian statistics to support regulatory evaluation of medical devices began in the late 1990s. We review the literature, focusing on recent developments of Bayesian methods, including hierarchical modeling of studies and subgroups, borrowing strength from prior data, effective sample size, Bayesian adaptive designs, pediatric extrapolation, benefit-risk decision analysis, use of real-world evidence, and diagnostic device evaluation. We illustrate how these developments were utilized in recent medical device evaluations. In Supplementary Material, we provide a list of medical devices for which Bayesian statistics were used to support approval by the US Food and Drug Administration (FDA), including those since 2010, the year the FDA published their guidance on Bayesian statistics for medical devices. We conclude with a discussion of current and future challenges and opportunities for Bayesian statistics, including artificial intelligence/machine learning (AI/ML) Bayesian modeling, uncertainty quantification, Bayesian approaches using propensity scores, and computational challenges for high dimensional data and models.

PMID:36869194 | DOI:10.1007/s43441-022-00495-w

Bone Marrow Transplant. 2023 Mar 3. doi: 10.1038/s41409-023-01935-3. Online ahead of print.

ABSTRACT

We are pleased to add this typescript, Inappropriate use of statistical power by Raphael Fraser to the BONE MARROW TRANSPLANTATION Statistics Series. The authour discusses how we sometimes misuse statistical analyses after a study is completed and analyzed to explain the results. The most egregious example is post hoc power calculations.When the conclusion of an observational study or clinical trial is negative, namely, the data observed (or more extreme data) fail to reject the null hypothesis, people often argue for calculating the observed statistical power. This is especially true of clinical trialists believing in a new therapy who wished and hoped for a favorable outcome (rejecting the null hypothesis). One is reminded of the saying from Benjamin Franklin: A man convinced against his will is of the same opinion still.As the authour notes, when we face a negative conclusion of a clinical trial there are two possibilities: (1) there is no treatment effect; or (2) we made a mistake. By calculating the observed power after the study, people (incorrectly) believe if the observed power is high there is strong support for the null hypothesis. However, the problem is usually the opposite: if the observed power is low, the null hypothesis was not rejected because there were too few subjects. This is usually couched in terms such as: there was a trend towards… or we failed to detect a benefit because we had too few subjects or the like. Observed power should not be used to interpret results of a negative study. Put more strongly, observed power should not be calculated after a study is completed and analyzed. The power of the study to reject or not the null hypothesis is already incorporated in the calculation of the p value.The authour use interesting analogies to make important points about hypothesis testing. Testing the null hypothesis is like a jury trial. The jury can find the plaintiff guilty or not guilty. They cannot find him innocent. It is always important to recall failure to reject the null hypothesis does not mean the null hypothesis is true, simply there are insufficient evidence (data) to reject it. As the author notes: In a sense, hypothesis testing is like world championship boxing where the null hypothesis is the champion until defeated by the challenger, the alternative hypothesis, to become the new world champion.The authour include a discussion of what is a p-value, a topic we discussed before in this series and elsewhere [1, 2]. Finally, there is a nice discussion of confidence intervals (frequentist) and credibility limits (Bayesian). A frequentist interpretation views probability as the limit of the relative frequency of an event after many trials. In contrast, a Bayesian interpretation views probability in the context of a degree of belief in an event . This belief could be based on prior knowledge such as the results of previous trials, biological plausibility or personal beliefs (my drug is better than your drug). The important point is the common mis-interpretation of confidence intervals. For example, many researchers interpret a 95 percent confidence interval to mean there is a 95 percent chance this interval contains the parameter value. This is wrong. It means, if we repeat the identical study many times 95 percent of the intervals will contain the true but unknown parameter in the population. This will seem strange to many people because we are interested only in the study we are analyzing, not in repeating the same study-design many times.We hope readers will enjoy this well-written summary of common statistical errors, especially post hoc calculations of observed power. Going forth we hope to ban statements like there was a trend towards… or we failed to detect a benefit because we had too few subjects from the Journal. Reviewers have been advised. Proceed at your own risk. Robert Peter Gale MD, PhD, DSc(hc), FACP, FRCP, FRCPI(hon), FRSM, Imperial College London, Mei-Jie Zhang PhD, Medical College of Wisconsin.

PMID:36869191 | DOI:10.1038/s41409-023-01935-3

J Gen Intern Med. 2023 Mar 3. doi: 10.1007/s11606-023-08094-7. Online ahead of print.

ABSTRACT

BACKGROUND: Habitually skipping breakfast may promote the initiation and progression of gastrointestinal (GI) cancers, which have never been systematically explored in large-scale prospective studies.

METHODS: We prospectively examined the effects of breakfast frequency on the occurrence of GI cancers among 62,746 participants. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) of GI cancers were calculated by Cox regression. The CAUSALMED procedure was used to perform the mediation analyses.

RESULTS: During a median follow-up of 5.61 (5.18 ~ 6.08) years, 369 incident GI cancer cases were identified. Participants who consumed 1-2 times breakfasts per week exhibited an increased risk of stomach (HR = 3.45, 95% CI: 1.06-11.20) and liver cancer (HR = 3.42, 95% CI: 1.22-9.53). Participants who did not eat breakfast had an elevated risk of esophageal (HR = 2.72, 95% CI: 1.05-7.03), colorectal (HR = 2.32, 95% CI: 1.34-4.01), liver (HR = 2.41, 95% CI: 1.23-4.71), gallbladder, and extrahepatic bile duct cancer (HR = 5.43, 95% CI: 1.34-21.93). In the mediation effect analyses, BMI, CRP, and TyG (fasting triglyceride-glucose) index did not mediate the association between breakfast frequency and the risk of GI cancer incidence (all P for mediation effect > 0.05).

CONCLUSIONS: Habitually skipping breakfast was associated with a greater risk of GI cancers including esophageal, gastric, colorectal, liver, gallbladder, and extrahepatic bile duct cancer.

TRIAL REGISTRATION: Kailuan study, ChiCTR-TNRC-11001489. Registered 24 August, 2011-Retrospectively registered, http://www.chictr.org.cn/showprojen.aspx?proj=8050.

PMID:36869181 | DOI:10.1007/s11606-023-08094-7

Sleep Breath. 2023 Mar 4. doi: 10.1007/s11325-023-02798-0. Online ahead of print.

ABSTRACT

PURPOSE: The relationships between sleep quality and sleep hygiene awareness in the Chinese population were unclear. We aimed to investigate the associations and related factors between sleep quality and sleep hygiene awareness in adults and to identify the most central domain for sleep quality using network analysis.

METHODS: A cross-sectional survey was conducted from April 22 to May 5, 2020. Adults (18 years old or above) who had access to smartphones were invited to participate in this survey. The Pittsburg Sleep Quality Index (PSQI) and the Sleep Hygiene Awareness and Practice Scale (SHAPS) were used to evaluate the sleep quality and sleep hygiene awareness of the participants. Propensity score matching (PSM) was used as sensitivity analysis to reduce the confounding effects. Multiple logistic regression was performed to evaluate the associations. The R packages “bootnet” and “qgraph” were used to estimate the connection and calculate the network centrality indices between good and poor sleepers.

RESULTS: In total, 939 respondents were included in the analysis. Of them, 48.8% (95% CI: 45.6-52.0%) were identified as poor sleepers. Participants with nervous system diseases, psychiatric diseases, and psychological problems were more likely to have poor sleep quality. The notion that using sleep medication regularly was beneficial to sleep was associated with poor sleep quality. Similarly, the notion that waking up at the same time each day disrupted sleep was also associated with poor sleep quality. The findings were consistent before and after PSM. Subjective sleep quality was the most central domain for sleep quality in good and poor sleepers.

CONCLUSION: Poor sleep quality was positively associated with certain sleep hygiene notions in Chinese adults. Effective measures such as self-relief, sleep hygiene education, and cognitive behavioral treatment may have been needed to improve sleep quality, especially during the COVID-19 outbreak.

PMID:36869169 | DOI:10.1007/s11325-023-02798-0

JCO Oncol Pract. 2023 Mar 3:OP2200341. doi: 10.1200/OP.22.00341. Online ahead of print.

ABSTRACT

PURPOSE: Despite more than a decade of endorsement from multiple international cancer authorities advocating all women with ovarian cancer be offered germline breast cancer (BRCA) gene testing, British Columbia Cancer Victoria was not meeting this target. A quality improvement project was undertaken with the aim of increasing completed BRCA testing rates for all eligible patients seen at British Columbia Cancer Victoria to > 90% by 1 year from April 2016.

METHODS: A current state analysis was completed, and multiple change ideas were developed, including education of medical oncologists, referral process update, initiating a group consenting seminar, and engagement of a nurse practitioner to lead the seminar. We used a retrospective chart audit from December 2014 to February 2018. On April 15, 2016, we initiated our Plan, Do, Study, Act (PDSA) cycles and completed them on February 28, 2018. We evaluated sustainability through an additional retrospective chart audit from January 2021 to August 2021.

RESULTS: Patients with completed germline BRCA genetic testing climbed from an average of 58%-89% per month. Before our project, patients waited on average 243 days (± 214) for their genetic test results. After implementation, patients received results within 118 days (± 98). This was sustained with an average of 83% of patients per month having completed germline BRCA testing almost 3 years after project completion.

CONCLUSION: Our quality improvement initiative resulted in a sustained increase in germline BRCA test completion for eligible patients with ovarian cancer.

PMID:36867837 | DOI:10.1200/OP.22.00341

Phys Rev Lett. 2023 Feb 17;130(7):071802. doi: 10.1103/PhysRevLett.130.071802.

ABSTRACT

An absolute measurement of the Λ_{c}^{+} lifetime is reported using Λ_{c}^{+}→pK^{-}π^{+} decays in events reconstructed from data collected by the Belle II experiment at the SuperKEKB asymmetric-energy electron-positron collider. The total integrated luminosity of the data sample, which was collected at center-of-mass energies at or near the ϒ(4S) resonance, is 207.2 fb^{-1}. The result, τ(Λ_{c}^{+})=203.20±0.89±0.77 fs, where the first uncertainty is statistical and the second systematic, is the most precise measurement to date and is consistent with previous determinations.

PMID:36867815 | DOI:10.1103/PhysRevLett.130.071802

Invest Educ Enferm. 2022 Oct;40(3). doi: 10.17533/udea.iee.v40n3e11.

ABSTRACT

OBJECTIVES: To evaluate the effectiveness of the application of an educational program based on the Health Belief Model (HBM) in Adopting Preventive Behaviors from Self-Medication among Women in Iran.

METHODS: Interventional study with pre and post phases. 200 women referring to the health centers of Urmia were selected by simple random sampling, divided into two groups of treatment and control. Data collection instruments were researcher-devised questionnaire including the questionnaire of Knowledge of Self-medication, the Questionnaire of Preventive Behaviors from Self-medication, and the questionnaire of Health Belief Model. The questionnaires were assessed for expert validity and then, were checked for reliability. The educational intervention was conducted for the treatment group during four weeks four 45-minute sessions.

RESULTS: The average scores of knowledge, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, self-efficiency, and post-intervention performance in have increased in treatment group, comparing to the control group, All findings were statistically significant (p < 0.05). Furthermore, social media, doctors, and disbelief in self-medication were more effective in increasing awareness and encouraging to have proper medication, also, the highest self-medication was in taking pain-relievers, cold tablets and antibiotics, which showed significant decrease in treatment group after the intervention.

CONCLUSIONS: The educational program based on Health Belief Model was effective in reducing the self-medication among the studied women. Furthermore, it is recommended to use social media and doctors to improve the awareness and motivation among people. Thus, applying the educational programs and plans according to the Health Belief Model can be influential in reducing the self-medication.

PMID:36867784 | DOI:10.17533/udea.iee.v40n3e11