During a median follow-up of 13 months (interquartile range: 6–20 months), 203 (3.5%) patients were lost to follow-up. MACEs occurred in 249 (4.3%) patients, including 11 (0.2%) cardiovascular deaths, 28 (0.5%) nonfatal MIs, 93 (1.6%) unstable angina hospitalization, and 117 (2.0%) late revascularizations.
UDFM classified more than half (1188/2078) the negative women into the medium PTP group, for which noninvasive testing was recommend according to the current guidelines. However, among the 1188 negative women, only 31 MACEs occurred (2.6%, one cardiovascular death, three nonfatal MIs, eight unstable anginas, and 19 late revascularizations). Use of DCS instead of UDFM would imply a change of diagnostic strategy in these negative women: 40% (471/1188) into the low PTP group, for which no further test was recommend. Moreover, among the 471 negative women, only seven MACEs occurred (1.5%, no cardiovascular death, one nonfatal MI, one unstable angina, and five late revascularizations).
In this CCTA-based analysis of patients with symptoms suggestive of stable CAD, we observed substantial sex-based differences in the clinical presentation and diagnostic evaluation. Although DCS seemed to perform better than UDFM with a positive NRI and IDI, neither of them showed a favorable AUC and calibration in women. Moreover, use of DCS instead of UDFM would alter the diagnostic strategy in women, resulting in a decrease in unnecessary testing. To our knowledge, this is the first comparative description of the sex-based differences in the calculation of PTP by the most proposed models, UDFM and DCS.
Consistent with our study, data from the PROMISE trial found that although women were more likely to be characterized as having a low PTP, they had larger traditional risk factor burden than men, except for BMI, diabetes, and smoking 6. Furthermore, previous investigations have suggested that the most common symptom type was atypical angina and women are more likely to present with atypical angina than men 6,25, which were similar to that noted in the present analysis. Thus, selection of optimal PTP models to ensure that they sufficiently account for the discrepancy between the higher prevalence of traditional risk factors and the lower reported prevalence of obstructive CAD is crucial in the development of a diagnostic strategy for women presenting with stable chest pain 5,6.
A number of previous studies have indicated that either UDFM or DCS overestimated the actual prevalence of obstructive CAD, especially in populations with low prevalence 13–17, which was confirmed by the unsatisfactory calibration in the current analysis, especially for women. By UDFM, more than half women were classified into the low PTP group, resulting in a marked underestimation manifested in the H-L calibration plots. Moreover, in women, the AUCs for both models were moderate (0.668 for UDFM and 0.654 for DCS), which was in line with a recently published study 26, yielding an AUC of 0.61 for UDFM and 0.59 for DCS in women referred to CCTA.
We noted two potential reasons for the unsatisfactory performance when applying the traditional age, sex, and chest pain typicality-based approach for women. First, the PTP models might show divergent predictions across patients differing only by sex 4. For example, according to UDFM, a 45-year-old female patient with atypical angina had a 14% PTP of obstructive CAD, whereas a male patient with same characteristics had a 38% PTP. It is worth noting that an 85-year-old female patient, who is the oldest patient in the present study with typical angina had a 76% PTP by UDFM. As a result, no woman had a PTP of more than 85% and was classified into the high PTP group. The reclassification table for women (Table 3) showed that more than half the negative and almost all the positive women were classified into the medium PTP group by UDFM.
Second, the prevalence of CCTA-based obstructive CAD did not correlate well with the presence or type of symptoms 25. The calculation of PTP by traditional models such as UDFM depended on a patient’s age, sex, and angina typicality 11. However, especially in women, a previous study had shown that patient symptoms categorized according to the classical definition 18 had a limited ability to predict obstructive CAD 25,27,28. This may be account for the unfavorable performance by UDFM in women, whereas DCS that include other risk factors and weakened prediction effect of angina typicality 19 improved the calculation accuracy of PTP with a positive NRI and IDI in this study. Similarly, Almeida et al.14 and Jensen et al.16 suggested that DCS seemed to perform better than UDFM in the prediction of obstructive CAD. It is worth noting that in the present research, DCS improved risk stratification through different mechanism pathways in men and women. DCS showed an NRI of 16.80% in men, which was ascribed to the reclassification of 30.91% (286/1184) of positive men to the higher PTP group, whereas 22.67% (471/2078) of negative women were reclassified into the lower PTP group, resulting in an NRI of 27.20%.
Recently, several large and real-world trials that were completed in symptomatic individuals showed low rates of cardiovascular event and positive noninvasive testing 22,27–29, especially in women 6,29. In conformity with this, according to the reclassification table in our study, UDFM classified more than half of the negative women into the medium PTP group, which was recommended to undergo noninvasive testing 7–9, and the MACE rate of these women was only 2.6%. In particular, noninvasive testing, especially stress testing, showed well-documented significant false-positive rates in women 5. Therefore, calculation of PTP by UDFM would lead to unnecessary testing and confounded approaches to the evaluation and diagnosis of obstructive CAD in women. Conversely, DCS classified most negative women into the low PTP group, resulting in a positive NRI. Moreover, the rate of MACEs in negative women reclassified into the low PTP group was extremely low. Thus, application of DCS instead of UDFM could alter the diagnostic strategy safely and effectively, leading to an evident decrease in unnecessary testing.
To increase the precision of PTP models in women, further studies may benefit from the following three factors. First, development of sex-specific equations is likely to contribute more toward balancing the variation by sex in the decision-making of the diagnostic strategy for CAD 30,31. Second, with the inclusion of some female-specific risk factors, such as estrogen status and gestational diabetes mellitus, the predictive ability of PTP models improved significantly 26,32. Third, novel markers, such as coronary artery calcium scores 13, which are manifestations of subclinical atherosclerosis, have shown the potential to improve the precision of PTP models. From a pathophysiological point of view, compared with risk factors, atherosclerosis per se is more reliable 33. Recently, using CCS, an extended model developed by Genders et al.17, improved the prediction compared with the clinical model (cross-validated c statistic improvement from 0.79 to 0.88, NRI 102%). Furthermore, an analysis involving data from the PROMISE study showed that addition of CCS improved differentiation and calibration of traditional PTP models in women 34.
The present study has limitations that warrant acknowledgement. First, this was a retrospective and single-center analysis. We focused on the initial presentation and evaluation for patients with symptoms suggestive of stable CAD, but those patients who were referred to other tests were excluded, resulting in a marked selection bias. Thus, further multicenter and prospective studies are needed. Second, although the scan was performed by an experienced technician and the image was evaluated by three physicians by consensus, CCTA may overestimate the possibility of obstructive CAD because of the excellent negative predictive value and the moderate positive predictive value compared with invasive coronary angiogram 35. Third, the conclusions of this study should be validated and confirmed in comparative cost-effectiveness analyses with long-term outcome data. Fourth, a new model, the PROMISE minimal-risk tool, was developed recently to identify patients with stable chest pain at very low risk of CAD and clinical events 36. This risk score provided a novel strategy to identify patients in whom noninvasive testing might be deferred safely and outperformed existing PTP models 37. Thus, more external validation investigations are needed in the future to determine whether the application of the PROMISE minimal-risk tool can reduce unnecessary testing safely and effectively, especially for women.
The clinical presentation and calculation of PTP differed significantly by sex in patients presenting with stable chest pain and referred to CCTA. Although the performance of neither model was satisfactory, DCS yielded a more accurate calculation of PTP than UDFM and application of DCS instead of UDFM would result in a significant decrease in inappropriate testing in women. These data suggest that continued investigations in this area are warranted to balance the sex-specific differences in the calculation of PTP.
This wok was funded by the Research Program of Tianjin Chest Hospital (no. 2018XKC10), the Key Program of Medical Industry of Tianjin (no. 16KG132), and grants from the Committee on Science and Technology, Jinnan District, Tianjin.
There are no conflicts of interest.
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