不同菌量负荷下Xpert MTB/RIF检测利福平耐药的效果评价

Effect of Xpert MTB/RIF on detection of rifampicin resistance under different bacterial loads

  • 摘要:
    目的 分析结核分枝杆菌(MTB)不同菌量负荷下Xpert MTB/RIF(简称Xpert)检测利福平耐药的可靠性, 为临床诊治提供参考。
    方法 选择2016年1月-2023年12月厦门大学附属第一医院分枝杆菌培养阳性的3 050份检测结果, 剔除220份非结核分枝杆菌后, 2 830份培养阳性标本进行Xpert检测, 其中阳性2 412份, 阴性418份。根据结核分枝杆菌菌量负荷大小分为高、中、低、极低4个处理组, 每组例数分别为552、916、656、288份。对培养阳性同时Xpert检测阳性的其中1 801株MTB菌株进行固体表型药物敏感试验。
    结果 高、中、低、极低4个处理组, 检测利福平的阳性率分别为10.33%(57/552)、11.14%(102/916)、8.54%(56/656)、8.68%(25/288)。以固体表型药物敏感试验结果为参考标准, 高、中、低、极低4个菌量负荷组中, Xpert检测利福平耐药的特异度和阴性预测值均>96%, 且差异均无统计学意义;各组灵敏度差异无统计学意义(P=0.053), 高菌量负荷的敏感度偏低, 为84.62%(44/52), 极低菌量负荷的敏感度仅为76.00%(19/25), 低于中菌量负荷的灵敏度为94.05%(79/84);各组阳性预测值(PPV)整体偏低, 但差异无统计学意义(P=0.239), 高、极低菌量组的PPV分别为77.19%(44/57)、76.00%(19/25)。4个菌量负荷组Xpert与固体表型药物敏感试验符合率均较高, 分别为94.95%(395/416)、97.51%(666/683)、96.75%(477/493)、94.26%(197/209), 差异无统计学意义(P=0.052), 从高菌量负荷到极低菌量负荷的Kappa值分别为0.778、0.889、0.831、0.727。Xpert与表型药物敏感试验结果不一致的菌株中, 高菌量负荷到极低菌量负荷, Xpert与基因芯片检测相比, 利福平结果一致率分别为81.82%(9/11)、100.00%(9/9)、100.00%(2/2)、25.00%(1/4)。
    结论 MTB极低菌量负荷时Xpert检测利福平发生假阳性和假阴性结果的概率均较高, 其次为高菌量负荷。中菌量负荷检测利福平耐药最可靠。

     

    Abstract:
    OBJECTIVE To analyze the reliability of Xpert MTB/RIF (referred to as Xpert) in detecting rifampicin resistance under varying bacterial loads of Mycobacterium tuberculosis (MTB) so as to reference for clinical diagnosis and treatment.
    METHODS A total of 3 050 mycobacterial culture-positive test results from Jan. 2016 to Dec. 2023 at the First Affiliated Hospital of Xiamen University were selected. After excluding 220 non-tuberculous mycobacteria cases, 2 830 culture-positive specimens underwent Xpert testing, with 2 412 positive and 418 negative cases. Based on MTB bacterial load, specimens were divided into four treatment groups-high, medium, low and very low-with 552, 916, 656 and 288 cases, respectively. Solid phenotypic drug susceptibility testing (DST) was performed on 1 801 MTB strains that were both culture-positive and Xpert-positive.
    RESULTS The positive rates of rifampicin in the high, medium, low and very-low treatment groups were 10.33% (57/552), 11.14% (102/916), 8.54% (56/656) and 8.68% (25/288), respectively. Using the solid phenotypic drug susceptibility testing results as the reference standard, the specificity and negative predictive value of Xpert for detecting rifampicin resistance in all four bacterial load groups exceeded 96%, with no statistically significant differences observed. No significant difference in sensitivity was noted among the groups (P=0.053), though the high bacterial load group exhibited relatively lower sensitivity at 84.62% (44/52), while the very-low bacterial load group showed the lowest sensitivity at 76.00% (19/25), which was lower than the medium bacterial load group′s 94.05% (79/84). The positive predictive values (PPV) across all groups were generally low but without statistically significant differences (P=0.239), with the high and very-low bacterial load groups registering PPVs of 77.19% (44/57) and 76.00% (19/25), respectively. The concordance rates of Xpert and solid phenotypic drug susceptibility testing were consistently high among all four bacterial load groups, including 94.95% (395/416), 97.51% (666/683), 96.75% (477/493) and 94.26% (197/209), respectively, with no significant difference(P=0.052). The Kappa values from high to very-low bacterial load groups were 0.778, 0.889, 0.831 and 0.727, respectively. Among the strains with discordant results between Xpert and phenotypic drug susceptibility testing, the rifampicin result consistency rates between Xpert and gene chip were 81.82% (9/11), 100.00% (9/9), 100.00% (2/2) and 25.00% (1/4), respectively for the high to very-low bacterial load groups.
    CONCLUSIONS When the bacterial load of MTB is very low, the Xpert assay demonstrates a higher probability of both false-positive and false-negative results for rifampicin resistance, followed by high bacterial loads. The most reliable detection of rifampicin resistance occurs with medium bacterial loads.

     

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