Can texture analysis of pre-immunotherapy CT imaging predict clinical outcomes for patients with advanced NSCLC treated with Nivolumab?

e20720 Background: Targeted therapies are ineffective in most NSCLC patients and response rates remain < 20% for patients with advanced NSCLC on immuno-monotherapy. Predictive models that distinguish responders from non-responders to immunotherapy could help guide clinical practice. Texture analysis is a data-mining tool used to identify intensity patterns in diagnostic imaging. We hypothesized that texture features on pre-immunotherapy CT imaging can be associated with clinical outcomes for patients with advanced NSCLC treated with Nivolumab. Methods: In an IRB-approved database containing 159 patients with advanced NSCLC treated with Nivolumab monotherapy, 20 patients with the longest overall survival (OS) and 20 with the shortest were selected for retrospective analysis. Patient characteristics were compared using paired t-tests. The last pre-immunotherapy PET CT for each patient was transferred to MIM software for segmentation. All FDG-avid intrathoracic tumors were delineated on the CT scan per RTOG contouring guidelines. Ninety-two texture features within each tumor were analyzed for association with the primary endpoint, OS. OS time was dichotomized to less than 1 year vs. more than 1 year. A univariate logistic regression model was used to estimate odds ratio (OR), 95% confidence interval and p-value for each feature. Multiple testing adjustments were performed using false discovery rate. Results: Eleven out of 92 texture features showed significant association with OS time (p-values from 0.009 to 0.044), of which 7 exhibited large effect (OR < 0.5 or > 1.5). Fifteen additional texture features trended toward statistical significance with p-values from .05 to .10. In all, 26 out of the 92 texture features showed significant association or trended toward significance with duration of OS. Conclusions: This preliminary study suggests that texture features on pre-immunotherapy CT imaging may help in predicting OS duration for patients with advanced NSCLC treated with Nivolumab monotherapy. We are in the process of validating a multivariate predictive model. Future directions include expansion of this study across the full database, survival analyses and correlation of texture features with tissue biology.

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Abstract MP11: Circulating Plasma Biomarkers Associated With Brain Arteriovenous Malformations

Stroke ◽

10.1161/str.52.suppl_1.mp11 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Sarah E Wetzel-Strong ◽

Shantel M Weinsheimer ◽

Jeffrey Nelson ◽

Ludmila Pawlikowska ◽

Dewi Clark ◽

...

Keyword(s):

Multiple Testing ◽

Statistical Significance ◽

Protein Profiling ◽

P Value ◽

P Values ◽

Plasma Biomarkers ◽

Standard Curve ◽

Disease States ◽

Heparin Plasma ◽

Circulating Levels

Objective: Circulating plasma protein profiling may aid in the identification of cerebrovascular disease signatures. This study aimed to identify circulating angiogenic and inflammatory biomarkers that may serve as biomarkers to differentiate sporadic brain arteriovenous malformation (bAVM) patients from other conditions with brain AVMs, including hereditary hemorrhagic telangiectasia (HHT) patients. Methods: The Quantibody Human Angiogenesis Array 1000 (Raybiotech) is an ELISA multiplex panel that was used to assess the levels of 60 proteins related to angiogenesis and inflammation in heparin plasma samples from 13 sporadic unruptured bAVM patients (69% male, mean age 51 years) and 37 patients with HHT (40% male, mean age 47 years, n=19 (51%) with bAVM). The Quantibody Q-Analyzer tool was used to calculate biomarker concentrations based on the standard curve for each marker and log-transformed marker levels were evaluated for associations between disease states using a multivariable interval regression model adjusted for age, sex, ethnicity and collection site. Statistical significance was based on Bonferroni correction for multiple testing of 60 biomarkers (P< 8.3x10 - 4 ). Results: Circulating levels of two plasma proteins differed significantly between sporadic bAVM and HHT patients: PDGF-BB (P=2.6x10 -4 , PI= 3.37, 95% CI:1.76-6.46) and CCL5 (P=6.0x10 -6 , PI=3.50, 95% CI=2.04-6.03). When considering markers with a nominal p-value of less than 0.01, MMP1 and angiostatin levels also differed between patients with sporadic bAVM and HHT. Markers with nominal p-values less than 0.05 when comparing sporadic brain AVM and HHT patients also included angiostatin, IL2, VEGF, GRO, CXCL16, ITAC, and TGFB3. Among HHT patients, the circulating levels of UPAR and IL6 were elevated in patients with documented bAVMs when considering markers with nominal p-values less than 0.05. Conclusions: This study identified differential expression of two promising plasma biomarkers that differentiate sporadic bAVMs from patients with HHT. Furthermore, this study allowed us to evaluate markers that are associated with the presence of bAVMs in HHT patients, which may offer insight into mechanisms underlying bAVM pathophysiology.

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The Conundrum of P-Values: Statistical Significance is Unavoidable but Need Medical Significance Too

Journal of Biostatistics and Epidemiology ◽

10.18502/jbe.v5i4.3862 ◽

2020 ◽

Author(s):

Abhaya Indrayan

Keyword(s):

Type I Error ◽

Dominant Role ◽

Statistical Significance ◽

Empirical Studies ◽

P Value ◽

Selective Reporting ◽

Type I ◽

Practical Application ◽

P Values ◽

Zero Effect

Background: Small P-values have been conventionally considered as evidence to reject a null hypothesis in empirical studies. However, there is widespread criticism of P-values now and the threshold we use for statistical significance is questioned.Methods: This communication is on contrarian view and explains why P-value and its threshold are still useful for ruling out sampling fluctuation as a source of the findings.Results: The problem is not with P-values themselves but it is with their misuse, abuse, and over-use, including the dominant role they have assumed in empirical results. False results may be mostly because of errors in design, invalid data, inadequate analysis, inappropriate interpretation, accumulation of Type-I error, and selective reporting, and not because of P-values per se.Conclusion: A threshold of P-values such as 0.05 for statistical significance is helpful in making a binary inference for practical application of the result. However, a lower threshold can be suggested to reduce the chance of false results. Also, the emphasis should be on detecting a medically significant effect and not zero effect.

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Clinical outcomes of elderly patients with esophageal cancer treated with chemoradiotherapy in the modern era.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.4_suppl.174 ◽

2017 ◽

Vol 35 (4_suppl) ◽

pp. 174-174

Author(s):

Cai Xu ◽

Mian Xi ◽

Amy Moreno ◽

Yutaka Shraishi ◽

Ritsuko Komaki ◽

...

Keyword(s):

Esophageal Cancer ◽

Elderly Patients ◽

Clinical Outcomes ◽

Concurrent Chemoradiotherapy ◽

Statistical Significance ◽

Concurrent Chemotherapy ◽

P Value ◽

Thoracic Esophageal Cancer ◽

Grade 3 ◽

Modern Era

174 Background: The optimal treatment approach is not clearly defined for elderly patients with esophageal cancer. We retrospectively analyzed the clinical outcomes of elderly patients ≥ 80 years old treated at a single institution in the modern era. Methods: Patients 80 years or greater with thoracic esophageal cancer who were treated consecutively with conventional modern radiotherapy (intensity-modulated radiation therapy or proton beam therapy) and concurrent chemotherapy between 2004 and 2016 were identified and included in this study. The one patient who had surgery was excluded. Toxicity was assessed using the CTCAE v.4.0. The rates of overall survival (OS) and recurrence free survival (RFS) were calculated with the Kaplan-Meier method. A p-value less than 0.05 indicated statistical significance. Results: Of the 1617 patients, 47 patients met the eligibility criteria. The median age was 81 years (range, 80-92 years). Most patients had some comorbid illnesses, with 81%, 9%, and 11% of patients having some cardiac, pulmonary, or diabetic related diseases, respectively. Twelve of 47 patients (26%) were given induction chemotherapy. The median dose was 50.4 Gy (range, 45 Gy-50.4 Gy). The clinical complete rate was 86%. With a median follow-up of 18 months (ranges, 1.9-117.6 months), the 2-year and 5-year OS was 54.5% and 27.7%, respectively, and the 2-year RFS was 63.6%. Three patients (6.4%) developed grade 3-5 radiation pneumonitis, with 2 (4.2%) being grade 5. Eighteen patients (38%) developed grade 1 pleural effusion, and 1 was grade 3. Three patients had grade 2 arrhythmia. Six patients had grades 1-2 pericardial effusion. One patient died from myocardial infarction. Four (9%) patients developed ≥ grade 3 esophagitis, with 7 patients having grade 3 esophageal stricture. Conclusions: The treatment of esophageal cancer patients 80 years or older with concurrent chemoradiotherapy was associated with an acceptable disease outcome, but the acute and late toxicities were higher than expected, which may be due to accompanying comorbidities. More research is needed to validate our observations and to better select patients who can optimally benefit from concurrent chemoradiotherapy.

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P values: from suggestion to superstition

Journal of Investigative Medicine ◽

10.1136/jim-2016-000206 ◽

2016 ◽

Vol 64 (7) ◽

pp. 1166-1171 ◽

Cited By ~ 13

Author(s):

John Concato ◽

John A Hartigan

Keyword(s):

Clinical Research ◽

Statistical Significance ◽

Historical Context ◽

P Value ◽

Threshold Probability ◽

Conceptual Approach ◽

P Values ◽

Clinical Investigations ◽

Current Usage ◽

Genomic Studies

A threshold probability value of ‘p≤0.05’ is commonly used in clinical investigations to indicate statistical significance. To allow clinicians to better understand evidence generated by research studies, this review defines the p value, summarizes the historical origins of the p value approach to hypothesis testing, describes various applications of p≤0.05 in the context of clinical research and discusses the emergence of p≤5×10−8 and other values as thresholds for genomic statistical analyses. Corresponding issues include a conceptual approach of evaluating whether data do not conform to a null hypothesis (ie, no exposure–outcome association). Importantly, and in the historical context of when p≤0.05 was first proposed, the 1-in-20 chance of a false-positive inference (ie, falsely concluding the existence of an exposure–outcome association) was offered only as a suggestion. In current usage, however, p≤0.05 is often misunderstood as a rigid threshold, sometimes with a misguided ‘win’ (p≤0.05) or ‘lose’ (p>0.05) approach. Also, in contemporary genomic studies, a threshold of p≤10−8 has been endorsed as a boundary for statistical significance when analyzing numerous genetic comparisons for each participant. A value of p≤0.05, or other thresholds, should not be employed reflexively to determine whether a clinical research investigation is trustworthy from a scientific perspective. Rather, and in parallel with conceptual issues of validity and generalizability, quantitative results should be interpreted using a combined assessment of strength of association, p values, CIs, and sample size.

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Visualization Strategies for Regression Estimates with Randomization Inference

10.31235/osf.io/bsd7g ◽

2019 ◽

Author(s):

Marshall A. Taylor

Keyword(s):

Confidence Interval ◽

Confidence Intervals ◽

Regression Models ◽

Statistical Significance ◽

Permutation Tests ◽

P Value ◽

P Values ◽

Alpha Level ◽

Significance Levels ◽

Nonprobability Sample

Coefficient plots are a popular tool for visualizing regression estimates. The appeal of these plots is that they visualize confidence intervals around the estimates and generally center the plot around zero, meaning that any estimate that crosses zero is statistically non-significant at at least the alpha-level around which the confidence intervals are constructed. For models with statistical significance levels determined via randomization models of inference and for which there is no standard error or confidence intervals for the estimate itself, these plots appear less useful. In this paper, I illustrate a variant of the coefficient plot for regression models with p-values constructed using permutation tests. These visualizations plot each estimate's p-value and its associated confidence interval in relation to a specified alpha-level. These plots can help the analyst interpret and report both the statistical and substantive significance of their models. Illustrations are provided using a nonprobability sample of activists and participants at a 1962 anti-Communism school.

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Risk factors for adverse clinical outcomes in patients with COVID-19: A systematic review and meta-analysis

10.1101/2020.05.13.20100495 ◽

2020 ◽

Cited By ~ 1

Author(s):

Vanesa Bellou ◽

Ioanna Tzoulaki ◽

Evangelos Evangelou ◽

Lazaros Belbasis

Keyword(s):

Risk Factors ◽

Systematic Review ◽

Clinical Outcomes ◽

Randomized Clinical Trials ◽

Clinical Decision Making ◽

Statistical Significance ◽

Specific Effect ◽

Chronic Obstructive ◽

P Value ◽

Meta Analyses

Importance: COVID-19 is a clinically heterogeneous disease of varying severity and prognosis. Clinical characteristics that impact disease course could offer guidance for clinical decision making and future research endeavors and unveil disease pathways. Objective: To examine risk factors associated with adverse clinical outcomes in patients with COVID-19. Data sources: We performed a systematic review in PubMed from January 1 until April 19, 2020. Study selection: Observational studies that examined the association of any clinical characteristic with an adverse clinical outcome were considered eligible. We scrutinized studies for potential overlap. Data extraction and synthesis: Information on the effect of clinical factors on clinical endpoints of patients with COVID-19 was independently extracted by two researchers. When an effect size was not reported, crude odds ratios were calculated based on the available information from the eligible articles. Study-specific effect sizes from non-overlapping studies were synthesized applying the random-effects model. Main outcome and measure: The examined outcomes were severity and progression of disease, admission to ICU, need for mechanical ventilation, mortality, or a composite outcome. Results: We identified 88 eligible articles, and we performed a total of 256 meta-analyses on the association of 98 unique risk factors with five clinical outcomes. Seven meta-analyses presented the strongest epidemiological evidence in terms of statistical significance (P-value <0.005), between-study heterogeneity (I2 <50%), sample size (more than 1000 COVID-19 patients), 95% prediction interval excluded the null value, and absence of small-study effects. Elevated C-reactive protein (OR, 6.46; 95% CI, 4.85 - 8.60), decreased lymphocyte count (OR, 4.16; 95% CI, 3.17 - 5.45), cerebrovascular disease (OR, 2.84; 95% CI, 1.55 - 5.20), chronic obstructive pulmonary disease (OR, 4.44; 95% CI, 2.46 - 8.02), diabetes mellitus (OR, 2.04; 95% CI, 1.54 - 2.70), hemoptysis (OR, 7.03; 95% CI, 4.57 - 10.81), and male sex (OR, 1.51; 95% CI, 1.30 - 1.75) were associated with risk of severe COVID-19. Conclusions and relevance: Our results highlight factors that could be useful for prognostic model building, help guide patients' selection for randomized clinical trials, as well as provide alternative treatment targets by shedding light to disease pathophysiology.

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P543Cardiac resynchronization therapy in left ventricular non-compaction: long-term results in a series of 40 patients

EP Europace ◽

10.1093/europace/euaa162.155 ◽

2020 ◽

Vol 22 (Supplement_1) ◽

Author(s):

D A Radu ◽

C N Iorgulescu ◽

S N Bogdan ◽

A I Deaconu ◽

A Badiul ◽

...

Keyword(s):

Statistical Significance ◽

Systolic Dysfunction ◽

Serum Levels ◽

Left Ventricular ◽

Long Term Results ◽

P Value ◽

P Values ◽

Mean Differences

Abstract Background Left ventricular non-compaction (LVNC) is a structural cardiomyopathy (SC) with a high probability of LV systolic dysfunction. Left bundle branch block (LBBB) frequently occurs in SCs. Purpose We sought to analyse the evolution of LVNC-CRT (LC) patients in general and compare it with the non-LVNC-CRT group (nLC). Methods We analysed 40 patients with contrast-MRI documented LVNC (concomitant positive Petersen and Jacquier criteria) implanted with CRT devices in CEHB. The follow-up included 7 hospital visits for each patient (between baseline and 3 years). Demographics, risk factors, usual serum levels, pre-procedural planning factors, clinical, ECG, TTE and biochemical markers were recorded. Statistical analysis was performed using software. Notable differences were reported as either p-values from crosstabs (discrete) or mean differences, p-values and confidence intervals from t-tests (continuous). A p-value of .05 was chosen for statistical significance (SS). Results Subjects in LC were younger (-7.52 ys; <.000; (-3.617;-11.440)), with no sex predominance, more obese (45.9 vs. 28.3%; <0.24) and had less ischaemic disease (17.9 vs. 39.7%; <.007). LC implants were usually CRT-Ds (91 vs. 49.5%; <.000) and more frequently MPP-ready (35.8 vs. 8.4%; <.000). At baseline, sinus rhythm was predominant in LC (97.4 vs. 79.8%; <.007) and permitted frequent use of optimal fusion CRT (75.5 vs. 46.6%; <.002). Although initial LVEFs were similar, LCs had much larger EDVs (+48.91 ml; <.020; (+7.705;+90.124)) and ESVs (+34.91; <.05; (+1.657;+71.478)). After an initial encouraging ⁓ 1 year evolution the LC-CRT group crashed its performance in terms of both LVEF and volumes. Thus, at 1 year follow-up, when compared to nLCs, LVEFs were far lower (-22.02%; <.000; (-32.29;-11.76)) while EDVs and ESVs much higher – (+70.8 ml; <.037; (+49.27;+ 189.65)) and (+100.13; <.039; (+5.25;+195)) respectively – in LCs in spite of similarly corrected dyssynchrony. The mean mitral regurgitation (MR) degree at 1 year was much higher in LCs (+1.8 classes; <.002; (+0.69;+2.97)) certainly contributing to the poor results. The cumulated super-responder/responder (SR/R) rates were constantly lower and decreasing at both 1 year (37.5 vs. 72.4; <.040) and 2 years of follow-up (10.1 vs. 80%; NS). Conclusions CRT candidates with LVNC are significantly more severe at the time of implant. After an initial short-term improvement (probably due to acute correction of dyssynchrony) most patients fail to respond in the long term. Severe dilation with important secondary MR probably plays an important role.

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H-Tuple Approach to Evaluate Statistical Significance of Biological Sequence Comparison with Gaps

Statistical Applications in Genetics and Molecular Biology ◽

10.2202/1544-6115.1272 ◽

2007 ◽

Vol 6 (1) ◽

Cited By ~ 1

Author(s):

Afshin Fayyaz movaghar ◽

Sabine Mercier ◽

Louis Ferré

Keyword(s):

Sequence Comparison ◽

Numerical Experiments ◽

Statistical Significance ◽

P Value ◽

Biological Sequence ◽

P Values ◽

Local Score ◽

Approximate Distribution ◽

Biological Sequence Comparison ◽

New Scoring

We propose an approximate distribution for the gapped local score of a two sequence comparison. Our method stands on combining an adapted scoring scheme that includes the gaps and an approximate distribution of the ungapped local score of two independent sequences of i.i.d. random variables. The new scoring scheme is defined on h-tuples of the sequences, using the gapped global score. The influence of h and the accuracy of the p-value are numerically studied and compared with obtained p-value of BLAST. The numerical experiments emphasize that our approximate p-values outperform the BLAST ones, particularly for both simulated and real short sequences.

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The Use of Biomarker Ferritin and Albumin As Well As HCT-CI, but Not PAM, Was Predictive of Suvival, Gvhd and, Relapse in Myeloid Malignancies

Blood ◽

10.1182/blood.v126.23.5448.5448 ◽

2015 ◽

Vol 126 (23) ◽

pp. 5448-5448

Author(s):

Gary Simmons ◽

Allison F. Scalora ◽

Roy T Sabo ◽

Catherine H. Roberts ◽

William B. Clark ◽

...

Keyword(s):

Overall Survival ◽

Stem Cell ◽

Stem Cell Transplantation ◽

Clinical Outcomes ◽

Serum Ferritin ◽

Risk Measure ◽

Patient Characteristics ◽

P Value ◽

Comorbidity Index ◽

Reduced Intensity

Abstract Developing the optimal models for pretransplant assessment as more reduced intensity conditioning regimens are implemented and the higher median age of transplant. The pre-transplant assessment of mortality (PAM) assesses all cause mortality at 2 years and the Hematopoietic Stem cell Transplantation specific comorbidity index (HCT-CI) which previously used Charlson comorbidity index (CCI) to assessed NRM based on history and organ function. Previous studies have shown that certain biomarkers such as ferritin and albumin may help optimize risk assessment before transplant. We tested the validity of PAM, HCT-CI, serum ferritin and albumin to predict GVHD, relapse and overall survival (OS) in our older patient population. IRB approval was obtained to retrospectively review clinical outcomes in patients undergoing allogeneic stem cell transplantation at our institution between, 2010 - 2013. We examined a total of 94 patients with myeloid malignancies (see Table 1 for patient characteristics). Risk variables assessed included calculated PAM, HCT-CI and KPS scores and pre HCT serum ferritin and albumin levels. We examined the predictive value of these biomarkers with respect to GVHD, relapse, and overall survival. Of the 94 patients 46% are alive and in remission, 20% have relapse and GVHD developed in 56% of patients. To determine the optimal cutoff for classifying into high and low groups for each risk measure, first the association between the measure and clinical outcomes was determined to obtain the logistic regression. Then area under the curve (AUC) of the receiver operating characteristic (ROC) curve for each clinical outcome against the risk measure was calculated. The cutoff that maximized the sum of the ROC-AUC across all measured was selected. Patients with HCT-CI > 4, (cut off 4), had a less likelihood of survival than those with HCT < 4 OR 4.3 (95% CI: 1.6-11.2) (p=.0033). Similarly, patients with low albumin, (cutoff 4.1), were less likely to than those with high albumin survive OR 0.4 (95% CI: 0.2-0.9) (p=0.02). Patients in the high ferritin group, (cut off 2425) were less likely to survive than those with low ferritin OR 4.0 (95% CI:1.3-2.3) (p=0.016). The high HCT-CI group, (cut off 4) was more likely to relapse than lower HCT-CI OR 2.9, (95% CI: 1.1-8.1) (p=0.04) and patients with a high KPS, (cutoff 81), were less likely to relapse than lower KPS OR 0.3 (95% CI: 0.1-0.8) (p=0.22). In the high ferritin group, (cutoff 2020) patients were more likely to have GVHD than low ferritin group OR 0.2 (95% CI: 0.1-0.7) (p=0.005). (Table 2) We conclude that HCT-CI was more predictive of mortality than the PAM score in our cohort or patients with median age 65 years old. Our results are concordant with previously reported data showing serum ferritin and albumin is useful biomarkers to predict GVHD, relapse and survival. We are now incorporating objective markers such as ferritin, albumin, and other functional assessments to objectively quantify risk in our current patients presenting for allogeneic HSCT. Table 1. Patient Characteristics All Patients (N = 94) N (%) Patient Age < 50 33 (35) 50-59 35 (37) 60-70 26 (28) Race Caucasian 76 (81) African American 14 (15) Other 4 (4) Donor Related 40 (43) Unrelated 54 (57) HLA Mismatch No 71 (76) Yes 10 (11) Missing 13 Stem Cell Source BM 5 (5) PBSC 89 (95) Conditioning Myeloablative 47 (50) Reduced Intensity 47 (50) ATG No 13 (14) Yes 81 (86) Patient CMV Sero status Negative 41 (44) Positive 48 (51) Missing 5 KPS < 90 17 (18) 90-100 77 (82) BM indicates bone marrow; PBSC, peripheral blood stem cells; CMV, cytomegalovirus. Table 2. Biomarkers and Clinical Outcomes Biomarkers GVHD Relapse Survival Cut-off p-value Cut-off p-value Cut-off p-value PAM 24 0.1222 24 0.4911 21 0.2077 HCT-CCI 2 03308 4 0.0495 4 0.0033 Ferritin 2020 0.0054 1070 0.3818 2425 0.0164 KPS 81 0.1679 81 0.0226 91 0.1289 Albumin 4.2 0.1103 4.2 0.2750 4.1 0.0220 Disclosures No relevant conflicts of interest to declare.

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Falacias sobre el valor p compartidas por profesores y estudiantes universitarios

Universitas Psychologica ◽

10.11144/javeriana.upsy16-3.fvcp ◽

2017 ◽

Vol 16 (3) ◽

pp. 1

Author(s):

Laura Badenes-Ribera ◽

Dolores Frias-Navarro

Keyword(s):

College Students ◽

Statistical Significance ◽

Psychological Research ◽

Practical Significance ◽

P Value ◽

P Values ◽

Statistical Education ◽

The Mean ◽

Estudiantes Universitarios

Resumen La “Práctica Basada en la Evidencia” exige que los profesionales valoren de forma crítica los resultados de las investigaciones psicológicas. Sin embargo, las interpretaciones incorrectas de los valores p de probabilidad son abundantes y repetitivas. Estas interpretaciones incorrectas afectan a las decisiones profesionales y ponen en riesgo la calidad de las intervenciones y la acumulación de un conocimiento científico válido. Identificar el tipo de falacia que subyace a las decisiones estadísticas es fundamental para abordar y planificar estrategias de educación estadística dirigidas a intervenir sobre las interpretaciones incorrectas. En consecuencia, el objetivo de este estudio es analizar la interpretación del valor p en estudiantes y profesores universitarios de Psicología. La muestra estuvo formada por 161 participantes (43 profesores y 118 estudiantes). La antigüedad media como profesor fue de 16.7 años (DT = 10.07). La edad media de los estudiantes fue de 21.59 (DT = 1.3). Los hallazgos sugieren que los estudiantes y profesores universitarios no conocen la interpretación correcta del valor p. La falacia de la probabilidad inversa presenta mayores problemas de comprensión. Además, se confunde la significación estadística y la significación práctica o clínica. Estos resultados destacan la necesidad de la educación estadística y re-educación estadística. Abstract The "Evidence Based Practice" requires professionals to critically assess the results of psychological research. However, incorrect interpretations of p values of probability are abundant and repetitive. These misconceptions affect professional decisions and compromise the quality of interventions and the accumulation of a valid scientific knowledge. Identifying the types of fallacies that underlying statistical decisions is fundamental for approaching and planning statistical education strategies designed to intervene in incorrect interpretations. Therefore, the aim of this study is to analyze the interpretation of p value among college students of psychology and academic psychologist. The sample was composed of 161 participants (43 academic and 118 students). The mean number of years as academic was 16.7 (SD = 10.07). The mean age of college students was 21.59 years (SD = 1.3). The findings suggest that college students and academic do not know the correct interpretation of p values. The fallacy of the inverse probability presents major problems of comprehension. In addition, statistical significance and practical significance or clinical are confused. There is a need for statistical education and statistical re-education.

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