“a numerical trend”

There was no main effect of list position, F (1,36) = 0.096, MSE = 0.634, p = 0.76, partial η 2 = 0.003 but a main effect of distraction, F (1,36) = 6.11, MSE = 0.585, p = 0.018, partial η 2 = 0.15 and a numerical trend towards an interaction of distraction with list position, F (1,36) = 3.46, MSE = 0.38, p = 0.071, partial η 2 = 0.09, as illustrated in Figure 3 .

There was a numerical trend towards increased Cannabis use by CD compared to UC patients (CD: 42, 37.8% vs UC:21 25.6%, P = 0.073).

Comparison of cell viability with the ConA group showed significant differences for the non-stimulated extract groups ( p < 0.05) and a numerical trend for the CC group ( p = 0.076).

Data showed, in patients for whom the assessment of thickness was possible at baseline and at 24 months, a numerical trend ( p = 0.076) towards a decrease at 24 months in the CS group versus the celecoxib group.

Although this association showed a numerical trend ( p = 0.076), it did not reach statistical significance at the predefined threshold.

Importantly, however, there was also a numerical trend towards an interaction of Time with Outcome valence ( F (1,18) = 3.51, p = 0.077, η 2 = 0.008), with average learning rates decreasing more for win ( t (39) = 2.79, p = 0.008) than loss outcomes ( t (39) = 0.64, p = 0.525) over time (see Fig. 3 b).

However, predicting acute scores was more accurate than predicting chronic scores for the within-group training ( z = 2.07, P < 0.0192) with a numerical trend for the between-group training ( z = 1.76, P < 0.0784).

TAPSE/PASP <0.32 showed a numerical trend toward higher mortality compared to the normal ratio (32.1% vs. 15.8%, p=0.0785), but this was not statistically significant, while moderate impairment (0.32-0.419) was comparable to normal level (18.9% vs. 15.8%, p=0.7727).

Combined treatment showed a numerical trend toward improved ORR (33.3% vs 16.0%, p = 0.08), but did not significantly prolong PFS compared to surufatinib monotherapy (9.7 vs 9.4 months, p = 0.64).

Among patients with lupus, there was a numerical trend towards an inverse correlation of Chao1 estimates of alpha diversity with SLEDAI score (Mann-Whitney, p=0.08) (data not shown).

At a 10% significance level, the CICRT group exhibited a numerical trend toward a greater reduction in residual tumor volume compared to the CCRT group (residual tumor volume 3.0% vs. 7.4%; p = 0.080, 95% confidence interval [CI]: −9.3%–0.6%, η 2 = 0.180); this met the pre‐specified threshold, although it did not reach the conventional 0.05 level.

In the ESUS group, outcomes between women and men did not differ significantly, although women showed a numerical trend toward higher disability (mean mRS, 2.6 vs. 2.1; p = 0.08).

Lastly, patients with de novo MBC did not have significantly different outcomes compared to those with recurrent disease, although there was a numerical trend toward improved PFS in the de novo group ( p = 0.081, Supplementary Fig. 1B, Supplementary Table 6).

76.1 months) and a numerical trend for a shorter OS (HR = 1.431, 95%CI:0.964-2.123, p = 0.081, median survival: 60.2 vs . 79.6 months) compared to MS1 patients (Fig. 1d, e ).

A numerical trend toward higher depressive disorder incidence with conventional therapy was observed in Cohort 2 (HR 1.96, p = 0.084), though this did not reach statistical significance. 3.4.2.

Myocardial work indices were also comparable (e.g., GWI p = 0.241), with a numerical trend toward lower GWE in women ( p = 0.084).

Instead, the model for the spillover region showed a numerical trend towards a main effect of PIM ( t = −1.80, p = .085) and a Match × RP positive interaction ( t = 1.97, p = .052).

However, the interim analysis of OS, while demonstrating a numerical trend in favor of the multimodal therapy strategy (HR: 0.80), did not cross the pre-specified boundary for statistical significance (P=0.087).

In contrast, although the pCR group showed a numerical trend toward improved RFS (p=0.088), this difference did not reach statistical significance.

did not find differences in restricted kidney function after birth between groups treated < 14 (0%), 14– ≤ 17 (14%), and > 17 (38%) weeks of gestation, but a numerical trend favoring earlier intervention was observed ( P = 0.089) [ 43 ].

Follow-up post hoc did not find any significant differences, although there was a numerical trend of post-training increase in the PMC tDCS group [ t (11) = 1.86, p = 0.09] but not in other two groups [both p s > 0.22].

The P + H arm showed a numerical trend without reaching statistical significance in 5-year DFS rate, compared to the H arm (RR 1.09, 95% CI 0.99–1.20, p = 0.09; Fig. 7 ).

We found a significant effect of CONDITION ( F (3,51) = 7.8, p < 0.001, η p 2 = 0.31, 95% CI [0.13, 0.54]) but only a numerical trend of cue-contingency SWITCH that did not reach significance at the chosen alpha level of 5% ( F (1,17) = 3.2, p = 0.09, η p 2 = 0.16, 95% CI [0.01, 0.46]) and no reliable interaction ( F < 1).

Nonetheless, at 1 year, a numerical trend towards a higher incidence of target lesion revascularizations was noted in the DCB group (22.1% vs. 13.5%; p = 0.09) [ 49 ].

In the subgroup of patients younger than 40 years old, a numerical trend was observed in favour of systemic therapy after primary surgery compared with systemic therapy alone in terms of BCSS (SHR: 0.81; 95% CI: 0.64–1.03; and P =0.09).