Excerpts

There was a significant trend of increasing mOS across all four subsets of GBM patients ( p = 0.019; TGFB2 lowMe / MGMT highMe predicted mOS of 21.1 months, patients with TGFB2 highMe / MGMT lowMe predicted mOS of 21.2 months) ( Figure 1 A).

However, this trend did not reach statistical significance at the interim analysis ( p = 0.019).

Highly significant differences between the two races were found in age ( p = 0.02), Gleason scores ( p = 0.01), and stage of disease ( p = 0.03).

There was also an increasing trend for both non-Indigenous and Indigenous populations in 18–50 years, with the Indigenous population having a higher AAPC (AAPC 1.88 (95%CI 0.28–3.51; p = 0.02) for non-Indigenous and AAPC 3.70 (95%CI 0.24–7.28; p = 0.04)) ( Supplementary Table S1 ). 3.1.2.

In head and neck squamous cell carcinoma, ROH was not significantly associated with cancer risk for females but was nominally significant for males ( p = 0.02 ) .

The Counterintuitive Survival Finding: A Statistical Artifact The nominally significant association between BAP1 loss and longer DFS (log-rank p = 0.020) directly contradicts the extensive literature establishing BAP1 loss as an adverse prognostic marker [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ].

LAG-3 levels were also elevated in total CD3+ T lymphocytes and CD8+ effector T cells, but it did not reach statistical significance in CD4+ T cells (MFI: 213.8 ± 16.7 vs. 151.3 ± 8.3, p = 0.02, 290.1 ± 23.5 vs. 188.7 ± 14.2, p = 0.005 and 176.7 ± 17.78 vs. 132.9 ± 6.3, p = ns, respectively) ( Figure 4 A,D).

Models 5 and 6, based on D mean,SMG, showed a significantly lower accuracies, compared to Model 3 ( p = 0.04 in both comparisons) and Model 8 ( p = 0.07 with a trend towards significance and p = 0.02, respectively). 3.3.

We could not find an interaction for aaCCI and oncological treatment but did find an interaction between age (older or younger than 70 years) and oncological treatment, which, however, was barely significant ( p = 0.02 for resection of metastasis; p = 0.01 for systemic treatment alone).

GVHD Univariate analysis showed that day 100 incidence of aGVHD grade II-IV was most prevalent in the Other cohort at 35.9%, with a decreasing trend observed among White (25.9%), South Asian (21.4%), East Asian (17.0%), and Black patients (16.3%), a statistically significant finding ( p = 0.02).

Had this patient been excluded from the analysis, the differences in PFS and OS between both (sub)populations would have been highly significant ( p = 0.021 and 0.0049, respectively).

The model demonstrated good discrimination (C-statistic = 0.72) with no global proportional hazards violation, although the cTOT variable showed a marginally significant time-dependent effect (Schoenfeld P = 0.022), consistent with a front-loaded benefit that attenuates as wounds approach complete healing.

In addition, an interesting finding was the lower number of infections after allo-HSCT in the exercise group, which remained quasi-significant after statistical adjustment ( p = 0.023 and 0.083 for total and viral infections, respectively).

Exo-miR-17-5p alone showed a slightly significant positive association with DFS by microarray data (HR = 1.253, p -value = 0.023, n = 67) but it was not associated with DFS by ddPCR data (HR = 1.028, p -value = 0.623, n = 63); however, when combined in a multivariable model, the HR of Exo-miR-17-5p became lower than “one” (i.e., negatively associated with DFS) and significant, underlying an interaction with miR-130a-3p that seems to balance its positive contribution to the final predictive score.

There was a weakly significant correlation (r = 0.41, p = 0.025) between Arg-1 H scores in the tumor parenchyma and stroma ( Supplementary Figure S1 ). 3.4.

However, there were four countries showing an increasing trend of ovarian cancer, including India (AAPC = 6.89, 95% C.I. 0.95 to 13.18, p = 0.028), Belarus (AAPC = 6.69, 95% C.I. 2.48 to 11.08, p = 0.002), African Americans in the United States: (AAPC = 4.90, 95% C.I. 0.50 to 9.48, p = 0.033), and Japan (AAPC = 4.00, 95% C.I. 0.88 to 7.21, p = 0.018). 4.

Notably, while the univariate analysis for TTF showed a numerical trend, the expanded multivariate Cox regression identified the combination regimen as a significant independent predictor of favorable TTF (HR 0.44, p = 0.028), representing a 56% reduction in the risk of treatment failure after adjusting for key confounders, including treatment era and prior biologic use.

The benefit for overall survival (HR 0.73 95%CI: 0.50–1.06) did not reach statistical significance ( p = 0.029, predefined as p < 0.01 in this meta-analysis).

When the specificity and accuracy of the consensus MR data were examined, the figures in our study outperformed those of the PET-CT alone, yielding highly significant differences in specificity ( p = 0.02926) and accuracy ( p = 0.0083).

SIRs by Time after Cholecystectomy The risk of ovarian cancer increased by 35% (95% CI 2% to 77%) in the first 6 months after cholecystectomy (95% CI did not include 1), but the risk increase did not reach statistical significance after multiplicity adjustment ( p -value = 0.03, Table 1 ).

Finally, the DFS Kaplan-Meier curves based on molecular classes did not provide a significant result in our patient cohort ( p = 0.12, Figure S1A ) while the ones based on their binary classification (i.e., P53 versus the other molecular classes) showed a significant trend ( p = 0.03 Figure S1B ). 4.

The mean AUCs of each compound might be higher in responding tumors ( Figure 4 C) and clearly significant for the mean AUC of D1 rapamycin ( p = 0.03).

A significant trend for lower non-relapse mortality was found from group 1 to group 4 (log-rank test for trend p = 0.03; Figure 3 A).

Even though the interim OS results of MONARCH-3 did not reach statistical significance (HR = 0.754, 95% CI 0.584–0.974, p = 0.0301), its absolute value is also very impressive, reaching 67.1 months.

As shown in Figure 4 A, our results suggested a significant or close-to-significant increase in lymphocyte count ( p = 0.031) and PNI ( p = 0.017) and decrease in NLR ( p = 0.070) and PLR ( p = 0.079) in good prognosis patients, whereas the change in the poor prognosis group was insignificant, suggesting that the change in these immune cell parameters can early predict the efficacy of DPP4-inhibitor on the prognosis of post-operative patients.