Arterial stiffening and peripheral wave reflections have been considered the major determinants of raised pulse pressure (PP) and isolated systolic hypertension, but the importance of cardiac contractility and ventricular ejection dynamics is also recognised.in silico using a cardiovascular model accounting for ventricular–aortic coupling. Reflections at the aortic root and from downstream vessels were quantified using emission and reflection coefficients, respectively.We examined the contributions of arterial compliance and ventricular contractility to variations in aortic flow and increased central (cPP) and peripheral (pPP) pulse pressure, and PP amplification (PPa) in normotensive subjects during pharmacological modulation of physiology, in hypertensive subjects, and 2) in aortic flow, leading to larger cPP (36.1 ± 8.8 vs. 59.0 ± 10.8 mmHg), pPP (56.9 ± 13.1 vs. 93.0 ± 17.0 mmHg) and PPa (20.8 ± 4.8 vs. 34.0 ± 7.3 mmHg). Increased compliance by vasodilation decreased cPP (62.2 ± 20.2 vs. 45.2 ± 17.8 mmHg) without altering in silico data obtained by independently changing contractility/compliance over the range observed in vivo.cPP was strongly associated with contractility and compliance, whereas pPP and PPa were strongly associated with contractility. Increased contractility by inotropic stimulation increased peak aortic flow (323.9 ± 52.8 vs. 389.1 ± 65.1 ml/s), and the rate of increase (3193.6 ± 793.0 vs. 4848.3 ± 450.4 ml/sVentricular contractility plays a key role in raising and amplifying PP, by altering aortic flow wave morphology. In vivo data was obtained in normotensive and hypertensive subjects; in the former, normal physiology was perturbed using vasoactive drugs with divergent effects on the heart and arteries. In silico data was simulated using a state-of-the-art model of cardiac dynamics coupled to a distributed model of arterial blood flow that enabled simulation of independent increases in either ventricular contractility or arterial stiffness that cannot be achieved in vivo. We examined the effects on central PP (cPP) and peripheral PP (pPP), PP amplification (PPa), and aortic flow of varying LV contractility or arterial stiffness, and studied the role played by aortic and peripheral wave reflections in raising cPP. Results showed that ventricular contractility plays a key role in raising and amplifying PP with hypertension.The purpose of the present study was to examine the contributions of LV contractility and arterial stiffness to variations in aortic flow wave morphology and increased PP and PP amplification, and describe the underlying hemodynamic mechanisms. Both 2.in vivo data, both invasive and non-invasive, was used to examine relationships between pressure and aortic flow  and hypertensive subjects  (The noninvasive ns ± SD) . CharactIn both cohorts, the carotid artery waveform was used as a surrogate for the aortic pressure waveform . Periphe2.3.We used a previously described computational model of blood flow in the 116 largest human arteries of the head, thorax, and limbs  , 24. Thein vivo normotensive cohort. To simulate the vasoactive effects of NA and GTN, and to a lesser extent of DB, arterial compliance was modified by changing either geometrical or mechanical vascular parameters of the 45–year–old baseline subject, namely arterial stiffness  or luminal diameters, spanning the range of age-specific mean values from the 25– to the 75–year–old baseline subjects  and the first systolic shoulder in central pressure (P1) (f) and backward (Pb) pressure components of the central pulse pressure wave, so that Pf + Pb = P−Pd with P the total blood pressure wave and Pd the diastolic blood pressure. Peripheral wave reflections were quantified by the peak reflection coefficient, b to that of Pf. The amount of BP “emitted” at the aortic root towards downstream vessels relative to the amount of BP reaching the aortic root from downstream vessels was calculated using the peak emission coefficient, f to that of Pb   with theure (P1) . Left–veure (P1) , which i (dP/dt) . Traditi (dP/dt)  was usedat of Pb . All sim2.5.t-tests. Baseline haemodynamic measures were compared with those measured at the maximum drug dose of GTN for the invasive cohort, and DB and NA for the normotensive cohort, and p < 0.05 was taken as significant. Correlation analyses were performed considering Pearson’s (R) and Spearman’s (rs) correlation coefficients. Pearson correlation evaluates the linear relationship between two continuous variables, whereas Spearman correlation evaluates their monotonic relationship (linear or not).Subject characteristics and results are presented as means ± SD. The effect of administering pharmacological drugs on haemodynamic measures was examined using paired 3.3.1.in vivo data . For all in vivo cohorts, PPa was moderately to strongly associated with s = −0.61 for the normotensive cohort, s = −0.30 for the hypertensive cohort). The correlations were the highest (R > 0.87 and rs < −0.61) for the measurements in normotensive subjects, in whom haemodynamics were perturbed and therefore the range of variation in Both cPP and pPP were moderately to strongly associated with p < 0.001) and led to larger cPP (36.1 ± 8.8 vs. 59.0 ± 10.8 mmHg), pPP (56.9 ± 13.1 vs. 93.0 ± 17.0 mmHg) and PPa (20.8 ± 4.8 vs. 34.0 ± 7.3 mmHg) (p < 0.001 each) in the normotensive cohort. In contrast, no significant changes in p < 0.001) and, to a smaller amount, by noradrenaline . In the invasive cohort, administration of glyceryl trinitrate significantly decreased cPP  and increased the time constant of the exponential decay of BP in diastole , which depends on arterial stiffness , the rate of increase in early–systolic aortic flow , and the rate of decrease in late–systolic aortic flow , without altering stroke volume (p = 0.78), whereas administration of noradrenaline did not affect these aortic flow measures (p = 0.007), rate of increase in early–systolic aortic flow , and rate of decrease in late–systolic aortic flow .mpliance . Adminismeasures . InteresIn silico results agreed with in vivo results. Variations of tic flow . In contconstant .3.3.In vivo pressure data from the normotensive cohort showed an increase in the first systolic shoulder (P1) and, to a lesser extent, the second systolic shoulder (P2) in central pressure with increasing dose of dobutamine . On the other hand, increasing dose of noradrenaline predominantly raised P2, and, to a lesser extent, P1  .ctively) . Figure In silico, independent changes in either contractility or compliance corroborated in vivo results. Increasing contractility, with compliance held constant, raised P1 and in vivo (in vivo data (2)  . pSBP annt as P1 . pSBP re3.4.In silico, these values were obtained with compliance held constant, which was not possible in vivo due to confounding factors. This led to comparable rates of increase in cPP, pPP and PPa than in the in vivo cohorts: 43, 73 and 28 mmHg, respectively, per unit increase in contractility . Therefore, at population level, the key role of contractility in raising and amplifying PP is corroborated. Moreover, the relationship between PPs and Within the range of contractility and compliance values measured in the normotensive and hypertensive cohorts of the study, cPP, pPP, and PPa showed a greater variation with contractility than compliance. This is in agreement with findings from the Framingham Heart study which analysed data from 6,417 healthy subjects and showed that a smaller change in CT study  conducteThis study has identified distinct hemodynamic mechanisms underlying the increases in cPP, pPP and PPa with contractility and compliance. We start with the mechanisms of cPP increase. Changes in contractility alter the aortic flow waveform in early systole, producing noticeable changes in peak aortic flow, rate of increase in early–systolic aortic flow, and rate of decrease in late–systolic aortic flow, corroborating previous studies on the strong relation between systolic flow ejection and PP , 17. Alt systole ], beforevia changes in in vivo with administration of the vasoconstrictor noradrenaline or the vasodilator GTN. Instead, compliance produced changes in aortic pressure in late systole, when the BP wave can be described by a space-independent Windkessel model , with pSBP2 having a smaller magnitude than the contractility-dependent pSBP. As a result, compliance affects mainly cPP rather than pPP, in agreement with results using a central-to-peripheral transfer function  on the central blood pressure wave and the peripheral systolic blood pressure (pSBP) on the peripheral pressure wave, both occurring in early systole. Therefore, pPP—and consequently PPa—is determined by a wave propagation phenomenon initiated by a change in aortic flow wave morphology: the propagation of the early systolic raise in BP towards the periphery. This finding aligns with experimental  and theofunction . The assfunction , where cfunction , 33, confunction , 34.In vivo measurements of pressure and aortic flow velocity were not simultaneous and inevitably subject to experimental error that can propagate when calculating flow derived quantities, such as rate of increase in early–systolic aortic flow. However, these errors are likely to be random and unlikely to influence the conclusions of our study which have also been confirmed by a physics-based cardiovascular model. In vivo, it is challenging to alter LV contractility through pharmacological interventions without affecting other haemodynamic properties, including arterial compliance, and vice-versa. Dobutamine does not affect uniquely inotropy and may have some vasodilator actions affecting compliance, and noradrenaline and glyceryl trinitrate do not affect uniquely compliance and may have some inotropic actions. Glyceryl trinitrate may elicit some activation of the sympathetic nervous system . The in silico model was therefore used to address this limitation of in vivo data in determining the extent PPs, PPa, and aortic flow depend on properties of the heart and arterial tree, by varying the cardiac and vascular parameters in isolation and avoiding in vivo confounding factors. Furthermore, arterial compliance was estimated as the ratio of stroke volume to cPP. However, this method does not account for arterial outflow in systole and may, therefore, overestimate compliance  than static  pathologies. Therefore, interventions that influence left ventricular contractility with a direct action on systolic ejection and aortic flow rate may be particularly effective in reducing PP and systolic hypertension, independent of vascular properties. Having established that peripheral systolic BP, which is used to assess clinical risk associated with hypertension and guide clinical care , is main6.in vivo and in silico data we have shown that ventricular contractility influences systolic ejection, shaping aortic flow morphology and playing a primary role in raising and amplifying pulse pressure. Arterial compliance was found to play a secondary role and peripheral wave reflections to play a minor role. Targeting ventricular contractility may be important in preventing and treating systolic hypertension.By using a complementary mix of


The wide use of antibody‐drug conjugates (ADCs) is transforming the cancer‐treatment landscape. Understanding the treatment‐related adverse events (AEs) of ADCs is crucial for their clinical application. We conducted a meta‐analysis to analyze the profile and incidence of AEs related to ADC use in the treatment of solid tumors and hematological malignancies.We searched the PubMed, Embase, and Cochrane Library databases for articles published from January 2001 to October 2022. The overall profile and incidence of all‐grade and grade ≥ 3 treatment‐related AEs were the primary outcomes of the analysis.I2 = 89%) and the incidence of grade ≥ 3 treatment‐related AEs was 6.2% .A total of 138 trials involving 15,473 patients were included in this study. The overall incidence of any‐grade treatment‐related AEs was 100.0% (95% confidence interval [CI]: 99.9%–100.0%; This study provides a comprehensive overview of AEs related to ADCs used for cancer treatment. ADC use resulted in a high incidence of any‐grade AEs but a low incidence of grade ≥ 3 AEs. The AE profiles and incidence differed according to cancer type, ADC type, and ADC components. The wide use of antibody‐drug conjugates is transforming the cancer treatment landscape. Understanding the treatment‐related adverse events of antibody–drug conjugates is crucial for clinical application. ADCsantibody‐drug conjugatesAEadverse eventCIconfidence intervalRCTsrandomized controlled trials1The emergence of antibody‐drug conjugates (ADCs) implied a paradigm shift in the treatment of many solid and hematologic malignancies. To date, 14 ADCs have been approved by the US Food and Drug Administration, the European Medicines Agency, National Medical Products Administration in China, and Japan's Ministry of Health, Labour and Welfare, for the treatment of solid tumors and hematological malignancies  prospective clinical trial for cancer treatment between January 2001 and October 2022; (2) treatment with single‐agent ADC; (3) ADC drugs approved by any governmental drug administration worldwide; (4) reported overall incidence or tabulated data on treatment‐related AEs; and (5) published in English. We excluded conference abstracts that did not contain detailed AE‐related data and that had <10 trial participants. The literature search, study selection, and data extraction were performed independently by two authors (G.S. and J.L.). Discrepancies were resolved by discussion with a third reviewer (Z.L.) until consensus was achieved. If multiple articles described the same trial, the article with the most recent and/or comprehensive AE data was used.2.2The trial name, first author, year of publication, region, ADC used, ADC component , trial phase, cancer type, study design, total number of participants, number of participants in safety analysis, arms and treatment, Common Terminology Criteria for Adverse Events (CTCAE) version, follow‐up time, and total number of all‐grade AEs were extracted for each study. The definitions of AEs were based on the Medical Dictionary for Regulatory Activities. Any‐grade, grade 3 or 4 AEs, and treatment‐related deaths were defined according to the CTCAE; treatment‐related AEs associated with treatment discontinuation were also extracted.2.3The primary outcome of interest was the overall incidence and profile of ADC‐related any‐grade and grade ≥ 3 AEs. The overall incidence and profile were determined by dividing the number of patients with all‐grade AEs by the total number of patients and the incidence of each specific AE, respectively. The incidence and profile of some specific AEs likely related to ADCs, subgroups according to cancer types, and the type of ADC drugs were analyzed. We also conducted subgroup analysis based on ADC components.2.4χ2 test and I2 statistic [I2 test. Statistical heterogeneity was defined as p < 0.1 and/or I2 > 50%. Publication bias was evaluated using a modified funnel plot of log odds against the sample size, because a conventional funnel plot against the standard error might be unreliable when the incidence is close to 0% or 100% [www.r-project.org) were used for meta‐analysis and forest plot construction, respectively. p < 0.05 was considered statistically significant.The effect size in our study was the incidence of AEs, obtained by dividing the number of participants with AEs by the total number of participants. Because the AE incidence did not follow a normal distribution, we performed logit conversion for AE incidence before the meta‐analysis , 14. Thetatistic . Heterog or 100% . Egger's or 100% . The met3n = 12), brentuximab vedotin (n = 32), trastuzumab emtansine (n = 17), inotuzumab ozogamicin (n = 11), moxetumomab pasudotox (n = 7), polatuzumab vedotin‐piiq (n = 1), enfortumab vedotin (n = 7), trastuzumab deruxtecan (n = 15), sacituzumab govitecan (n = 11), belantamab mafodotin‐blmf (n = 6), loncastuximab tesirine‐lpyl (n = 5), tisotumab vedotin‐tftv (n = 5), disitamab vedotin (n = 8), and RM‐1929 (n = 1). The basic characteristics of the included studies are shown in Table n = 28), cervical cancer (n = 5), gastric cancer or other solid tumors (n = 10), urothelial carcinoma (n = 12), lung cancer (n = 6), head and neck squamous cell carcinoma (n = 2), lymphoma (n = 34), leukemia (n = 35), and multiple myeloma (n = 6). In total, 138 trials  and 110 trials  were included for analyses of the profile and overall incidence of ADC‐related AEs, respectively.Figure 3.1In general, these studies reported >300 types of AEs. A total of 14,320 (92%) among 15,473 participants from 138 studies experienced at least one any‐grade AE and 2,695 (20.57%) of 13,101 participants from 98 studies experienced at least one grade ≥ 3 AE. Considering that this study mainly focused on grade ≥ 3 and any‐grade AEs, and we restricted ADC‐related AEs to the 28 most common, important, or specific AEs.I2 = 89%) and that of grade ≥ 3 treatment‐related AEs was 6.2% . A random‐effects model was used for analyses when p ≤ 0.10 or when the I2 statistic indicated >50% study heterogeneity. According to body systems, the most frequently reported any‐grade AEs were gastrointestinal AEs , followed by other , hematologic , ophthalmic , neurologic , dermatological , respiratory , and cardiovascular  AEs.Figure The most commonly reported all‐grade AEs occurring in ≥20% of patients were decreased platelet count , fatigue , peripheral edema , nausea , peripheral sensory neuropathy , decreased neutrophil count , alopecia , and decreased appetite   after trim and fill correction. No obvious asymmetry was observed in the modified funnel plots for grade ≥ 3 AEs . Because obvious heterogeneity was observed in the incidence of all‐grade and Gade ≥ 3 AEs across arms, we performed subgroup analyses to explore the source of heterogeneity.There was obvious asymmetry in the modified funnel plots for all‐grade AEs Figure  with p <s Figure   trials reporting the incidence of ADC‐related AEs were included.The most frequently reported any‐grade AE was ophthalmic toxicity , followed by hepatotoxicity , peripheral neuropathy , severely decreased neutrophil count , left cardiac dysfunction , diarrhea , dermatological reactions , and interstitial lung disease and pneumonitis  Figure . The mos3.3n = 129) was interstitial lung disease , followed by decreased platelet count , dyspnea , decreased neutrophil count , and pneumonia    and hematological malignancies . Among solid tumors, the most frequently reported any‐grade AEs were gastrointestinal AEs , followed by other , hematologic , and neurologic  AEs, and grade ≥ 3 AEs accounted for 3.5% of all AEs (95% CI: 1.2%–9.3%). Among hematological malignancies, the most frequently reported any‐grade AE was ophthalmic toxicity , followed by other , gastrointestinal , hematologic , and neurologic  AEs; grade ≥ 3 AEs accounted for 10.6% of all AEs (95% CI: 3.9%–25.7%)  for loncastuximab tesirine, 44.0% (95% CI: 10.1%–84.6%) for gemtuzumab ozogamicin, 36.4% (95% CI: 17.4%–60.9%) for disitamab vedotin, 33.8% (95% CI: 9.3%–71.8%) for inotuzumab ozogamicin, and 10.5% (95% CI: 0.9%–59.0%) for sacituzumab govitecan, whereas the incidence of grade ≥ 3 AEs for other ADCs was <10%  of antibodies in solid tumors, and the incidence of grade ≥ 3 AEs was evaluated according to nine types of antibodies, two types of linkers (cleavable and noncleavable), and five types of payload  Supporting Information: eTables 4Several ADCs have been approved by drug administrations and have been widely used in clinical trials and emerging studies worldwide. Despite the increased focus by clinicians and researchers on the safety of ADCs, however, a comprehensive AE profile for ADCs remains to be clearly defined. To the best of our knowledge, the current study was the first to analyze the incidence of ADC‐related AEs in studies published to date. The results showed that patients treated with ADCs had a high overall incidence of any‐grade AEs but a relatively low incidence of grade ≥ 3 AEs. Several ADC‐related special interest AEs were noted, as well as differences in the incidences of any‐grade and grade ≥ 3 AEs among different cancer types, ADC types, and ADC components.ADCs are typically composed of an antibody and a cytotoxic payload linked via a chemical linker . The speTo the best of our knowledge, only one previous meta‐analysis, including 70 publications, has evaluated the incidence of ADC‐related AEs, which concluded that most grade 3 and 4 ADC‐associated toxicities were related to the payload . HoweverIn the present study, the overall incidence of any‐grade AEs was 100.0% (95% CI: 99.9%–100.0%) and that of grade ≥ 3 AEs was 6.2% (95% CI: 3.0%–12.4%). Decreased platelet count was the most common any‐grade AE (34.9%) and the most common grade ≥ 3 AE (20.1%). Although less likely to be severe at presentation, the incidence of decreased platelet count was relatively high and is thus worth disclosing to patients. Fatigue, peripheral edema, nausea, peripheral sensory neuropathy, decreased neutrophil count, alopecia, and decreased appetite were the next most common any‐grade AEs; however, the likelihood of patients experiencing serious manifestations of these AEs is relatively low. Decreased neutrophil count, anemia, leukopenia, and fatigue are common grade ≥ 3 AEs, and patients should not be overly concerned about these AEs related to the cytotoxicity induced by ADC drug linkage.Our meta‐analysis also identified some special interest ADC‐related AEs that were less associated with chemotherapy or targeted agents but more common among ADC drugs, including hepatotoxicity, ophthalmic toxicity, dermatological reactions, left cardiac dysfunction, interstitial lung disease and pneumonitis, diarrhea, severely decreased neutrophil count, and peripheral neuropathy. Ophthalmic toxicities caused by ADC drugs are mainly related to the payload (MMAF), which can damage corneal epithelial cells , 163. FuThis meta‐analysis indicated several fatal toxic events of ADCs, with an overall mortality of 0.4%. Interstitial lung disease was the most common cause of ADC‐related death, followed by decreased platelet count, dyspnea, and decreased neutrophil count. Recognizing the profile of fatal toxic events is crucial for facilitating their early detection and effectively managing these events. Notably, although clinicians have been familiar with relatively common fatal toxic events such as pneumonitis, some rare fatal events, including diarrhea and dermatological reactions, should also be routinely screened.Subgroup analyses of the overall AE incidence based on cancer type, ADC type, and ADC components indicated significant differences in all cases. Overall, nine types of cancers were treated with 14 types of ADCs. Among solid tumors, the most frequently reported any‐grade AEs were gastrointestinal and hematologic AEs. Among patients with hematological malignancies, the most frequently reported any‐grade AEs were ophthalmic and gastrointestinal AEs. grade ≥ 3 AEs accounted for <11% of all AEs for both solid and hematological tumors. The choice of ADC drug target and antibody quality determine the affinity of the ADC for tumor cells, the type of linker determines the stability of the drug, and the choice of payload determines the AEs of ADCs . Eleven Different ADC components have markedly distinct AE spectra, as observed in the comparison between noncleavable and cleavable linkers. Noncleavable linkers are stable in plasma but have limited efficacy at the target cell, while cleavable linkers are unstable in plasma, leading to off‐target toxicity, but have higher efficacy at the target cell , 173. OuPayload analysis revealed the highest difference in the overall incidence of any‐grade and grade ≥ 3 AEs. Most payloads used in ADCs are highly cytotoxic and mediate the AEs of most ADCs. Our results showed that various payload was associated with an increased risk of any‐grade AEs, and PBD dimer SG3199 and calicheamicin were associated with increased risks of grade ≥ 3 AEs. SN‐38, PBD dimer SG3199, and MMAEs cause adverse respiratory effects, such as pneumonia, skin toxicity, and neurotoxicity, while deruxtecan, camptothecin, SN‐38, and calicheamicin mainly cause hematologic toxicity and MMAF causes ophthalmic toxicity. Most payloads can cause digestive and other toxicities, but have low cardiovascular toxicity.This study had some limitations. First, the diagnosis of AEs was evaluated by the original investigators in the different trials with no standardized or uniform definitions and/or classification. Moreover, the judgment of whether or not an AE was associated with an ADC might be susceptible to bias. There may also be overlap in the extraction process of adverse reaction data, such as elevated liver function indicators, hepatotoxicity, and ADC‐related hepatitis. Second, there was heterogeneity among the included trials with regard to targeted drugs, linkers, payload of ADCs, enrolled population, and number of treatment lines. We conducted multiple subgroup analyses to validate the results; however the limited number of included studies meant that we could not analyze several subgroups, for example, whether AEs were caused by a particular ADC component or by a combination of drug and disease factors. Finally, the number of trials of several ADCs was limited. Additional studies with larger sample sizes are therefore needed to confirm our findings.5This systematic review and meta‐analysis summarized the profile of AEs associated with ADC use and the common causes of treatment‐related death. ADCs were associated with a high incidence of any‐grade AEs but a relatively low incidence of grade ≥ 3 AEs. The type of cancer, type of ADC, and ADC components were associated with varying profiles and incidences of AEs. These findings regarding ADC‐related AEs may be useful for clinicians and researchers.Jinming Li, Guoshuang Shen, and Zhen Liu: Data curation ; writing—original draft . Yaobang Liu: Formal analysis ; writing—review and editing . Miaozhou Wang, Fuxing Zhao, and Dengfeng Ren: Conceptualization ; methodology . Qiqi Xie and Zitao Li: Data curation (supporting); software (supporting). Zhilin Liu: Resources (supporting); validation (supporting). Yi Zhao: Investigation (lead); supervision (lead). Fei Ma: Project administration (lead); writing—review and editing (lead). Xinlan Liu and Jiuda Zhao: Conceptualization (lead); project administration (lead).Cancer Innovation Editorial Board. To minimize bias, they were excluded from all editorial decision‐making related to the acceptance of this article for publication. The remaining authors declare no conflict of interest.Professor Fei Ma and Jiuda Zhao are the members of the This study used statistical methods to quantitatively synthesize the results of several independent clinical studies addressing the same clinical problem. The study did not involve human participation and was therefore exempt from the need for IRB review.Not applicable.eTable 1. Characteristics of components of antibody‐drug conjugates.Click here for additional data file.eTable 2. Search process.Click here for additional data file.eTable 3. Components of ADCs.Click here for additional data file.eTable 4. Incidence and types of treatment‐related adverse events according to cancer type and ADC component.Click here for additional data file.eFigure 1. Incidence of treatment discontinuation and treatment‐related deaths.Click here for additional data file.eFigure 2. Overall incidence of adverse event according to cancer type. (A) Incidence of adverse events of all grades in patients with solid tumors and hematologic malignancies; (B) incidence of adverse events of grade ≥3 in patients with solid tumors and hematologic malignancies.Click here for additional data file.eFigure 3. Overall incidence of adverse events based on ADC type. (A) Incidence of all grade adverse events based on ADC type; (B) incidence of grade ≥3 adverse events based on ADC type.Click here for additional data file.eFigure 4. Overall incidence of adverse events based on antibody. (A) Incidence of all grade adverse events based on antibody; (B) incidence of grade ≥3 adverse events based on antibody.Click here for additional data file.eFigure 5. Overall incidence of adverse events based on linker. (A) Incidence of all grades of adverse events based on linker; (B) incidence of grade ≥3 adverse events based on linker.Click here for additional data file.eFigure 6. Overall incidence of adverse events based on payload. (A) Incidence of all‐grade adverse events based on payload; (B) incidence of grade ≥3 adverse events based on payload.Click here for additional data file.Supporting information.Click here for additional data file.


DI) on soil bacterial diversity as well as the soil bacterial community assembly process and the factors influencing it. The results showed that long-term DI substantially reduced soil salinity and increased soil bacterial diversity while affecting the soil bacterial community structure distinctly. Null model results showed that the soil bacterial community assembly transitioned from stochastic processes to deterministic processes, as NDI increased. Homogeneous selection, a deterministic process, emerged as the dominant process when NDI exceeded 15 years. Both random forest and structural equation models showed that soil salinity was the primary factor affecting the bacterial community assembly process. In summary, this study suggested that soil bacteria respond differently to long-term DI and depends on the NDI, influencing the soil bacterial community assembly process under long-term DI.Identifying the potential factors associated with the impact of long-term drip irrigation (DI) on soil ecosystems is essential for responding to the environmental changes induced by extensive application of DI technology in arid regions. Herein, we examined the effects of the length of time that DI lasts in years (N All the XPCC farms were irrigated and fertilized simultaneously. The applied fertilizer primarily comprised urea (CO(NH2)2), with a nitrogen content of 46%, and potassium dihydrogen phosphate (KH2PO4), with a P2O5 content of 51.5%. Urea and potassium dihydrogen phosphate were applied at rates of 390–585 kg/hm2 and 240–330 kg/hm2, respectively, throughout the entire growth period.Since farms used to be saline wastelands prior to their reclamation in 1997. Following the adoption of DI technology, these farms have been cultivated with cotton crops. Two planting patterns of “one mulch, two tapes, and four rows” and “one mulch, three tapes, and six rows,” were characterized by a mulch width of 120 cm and 210 cm, respectively, and an inter-mulch bare ground width of 60 cm, had been used successively . Each XPDI values, based on the number of years of application of DI technology, in conjunction with the local land management model. Because the different size of all farms according to the actual local situation, three sampling sites with 10, 15, and 20 years of DI application at Point_A were selected, three sampling points with 15, 18, and 25 years of DI application at Point_B were selected, four sampling sites with 8, 10, 15, and 20 years of DI application at Point_C were selected, and four sampling sites with 5, 10, 15, and 20 years of DI application at Point_D were selected, respectively. The fields were categorized by their N2.2.4+ and NO3− and enzyme activity analyses and the other part was stored at −80°C for soil microbial community analyses.All soil samples used in this study were collected in the topsoil (0–20 cm depth) by using multi-point sampling method at the cotton Flower stages. Cutting ring method was used to determine soil volumetric mass at the same time. A total of 84 samples were obtained. The soil samples were classified into three parts, one of which was dried and used for the measurement of physicochemical properties. The second part was stored at 4°C for NH4+ and NO3− analyses were conducted on the obtained supernatant utilizing an AA3-HR Continuous Flow Analyzer . A UV–visible spectrophotometer (UV-1200) was utilized to determine the concentration of phosphorus that is readily accessible in the soil. Oven drying technique was used to quantify the soil moisture. Soil organic matter (OM) was determined by the Walkley–Black dichromate oxidation method . We mixed 10 g of the fresh soil with 50 mL of 2 M KCl solution (superior pure GR) in a trigonometric bottle with a capacity of 50 mL and agitated for 15 min (200 rpm) at ambient temperature. After that, the NHn method . Total nn method . Total pn method . Availabn method . Availabn method . The soin method . Soil pH2.3.® SPIN Kit for Soil , total DNA was isolated from the second subsample of each soil sample. The soil loading weight for DNA extraction is 0.25 g for each sample. The NanoDrop 2000 was adopted to estimate the concentration and purity of the DNA, and the 2% agar-gel electrophoresis method was applied to determine the DNA’s quality. The barcode sequence was included in the process so that sequencing data could be differentiated across samples in 0–20 cm soil layer. Rimers 341F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) were utilized to amplify the bacterial 16S rRNA gene’s V3-V4 region for each sample . The overall amount of the amplification system was 20 μL, and it contained the following, which comprised 10 ng of DNA template, 4 μL of 5 × Fast Pfu buffer, 0.4 μL of Fast Pfu polymerase, 0.8 μL of primer (5 μM), and 2 μL of 2.5 mm dNTPs. In addition, 2% agarose gel was utilized to extract PCR products, which were then purified utilizing an Axy Prep DNA Gel Extraction Kit , rinsed in Tris–HCl, and finally identified by electrophoresis on a second 2% agarose gel. Subsequent DNA quantification was done with QuantiFluor™-ST . Depending on the sequencing needs and the quantification findings, PCR products were processed to create sequencing libraries. An Illumina NovaSeq 6,000 sequencing system was adopted to sequence the resulting libraries.With the aid of a FastDNAh sample . The proSequencing libraries were filtered to exclude reads with poor quality characteristics such as a low mean Phred score < 20, ambiguous bases, homopolymer runs longer than 6 bases, short sequence lengths (less than 150 bp), and primer mismatches . Additio2.4.DI values were generated using R (v4.0.2), and the effects of these parameters were statistically examined via a Tukey’s true significant difference (HSD) test. Principal coordinate analysis (PCoA) and a two-way Adonis test from the “vegan” package in R were conducted to evaluate the variations in the composition of soil microbial population across different time points and NDI values (v4.0.2). By employing the “ggplot2” and “vegan” packages in R (v4.0.2), we performed a redundancy analysis (RDA) to verify the associations of soil microbial populations with soil characteristics.QIIME v1.92 was adopted to compute the Shannon and Chao1 indexes, two measures of the alpha (𝛼) diversity of the soil bacterial community . BoxplotRandom forest analysis was conducted to identify soil properties most strongly linked to bacterial community variation. Linear regressions between actual and predicted PC1 scores for bacterial communities were used to assess the validity of soil properties in evaluating bacterial communities. By measuring the increase in the mean square error when the response variable of each predictor was replaced 999 times at random, we could determine which predictors were the most significant in determining bacterial composition. Finally, the influence of soil characteristics on bacterial community diversity and composition was quantified using structural equation modeling conducted with the “lavven” software package.3.3.1.p < 0.05), and a higher pH than those at Point_B and Point_D (p < 0.05). The available phosphorus (AP) in Point_A and Point_D was higher than that in the other two sampling sites (p < 0.05). The soil samples at Point_A had a significantly higher total dissolved solids (TDS) than those at Point_D (p < 0.05). The soil pH did not vary considerably with NDI. The TDS content of the soils decreased significantly when NDI exceeded 15 years, whereas the TP content increased considerably when NDI exceeded 10 years (p < 0.05). The peroxidase (POD) and urease activity of the soils did not vary considerably with the sampling point and NDI. The soil that was subjected to DI for 18 years, had the lowest ALP and PPO activity  revealed that the dissimilarly of soil bacterial community composition changed with time (p = 0.001), AK (p = 0.001), and TP (p = 0.001) had a highly significant impact on the differences in soil bacterial communities.With Nith time . A correith time . TDS  value decreased continuously, and the median betaNTI value for each soil sample was lower than −2  of each soil bacterial community were predicted by the random forest model based on soil environmental factors . The pre4.4.1.DI under scrutiny. The outcomes of the present investigation showed that soil salinity subjected to NDI < 10 years had a considerably higher salinity content than those subjected to NDI > 10 years (MDI plays a crucial role in regulating water and salt transport in irrigated agriculture in arid regions . MDI is 10 years . ConsequDI not only creates a suitable water and salt environment for the crop root zone but also affects soil microorganisms while ameliorating the physical and chemical properties of the soil . The res4.2.p = 0.001; Nonetheless, the extent to which salinity levels constitute the primary determinant influencing the configuration of the microbial community structure remains a subject of ongoing debate. Notably, certain contemporary discoveries postulate an alternative perspective, contending that the intricate framework of the microbial community structure within the soil is distinctly shaped by variables encompassing soil moisture content, pH levels, and nutrient concentrations, supplanting salinity as the paramount factor in this context . Soil baDI < 15 years, whereas deterministic processes played an increasingly critical role as NDI increased (DI increases, which is consistent with the results of DI of 15 years. Marked changes in environmental factors may induce deterministic processes, which may be the cause of the increase in deterministic processes at NDI > 15 years. Moreover, homogeneous selection leads to a more similar microbial community structure, contributing to a more stable soil bacterial community (Stochastic and deterministic processes play different roles in the soil microbial community assembly, depending on environmental conditions, the successional stage, and the type and level of disturbance . The resncreased . This suommunity . In thisommunity , and to ommunity , respectommunity .5.DI > 10 years while affecting the soil bacterial community structure distinctly. The null model results showed that homogeneous selection was the dominant process at NDI > 15 years. Both random forest and structural equation models showed that soil salinity was the primary factor impacting the bacterial community assembly process. These results provide new insights into the sustainable productivity of agricultural ecosystems in arid regions and can further facilitate the sustainable development of drip-irrigated agricultural ecosystems in arid regions.The results showed that long-term DI substantially reduced soil salinity and considerably increased soil bacterial diversity at NThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.DL: Conceptualization, Investigation, Writing – original draft. HQ: Data curation, Writing – review & editing. GT: Formal analysis, Methodology, Writing – review & editing. YZ: Writing – review & editing. XZ: Investigation, Writing – review & editing. SH: Formal analysis, Writing – review & editing.


Molecular profiling has been applied for uterine corpus endometrial carcinoma (UCEC) management for many years. The aim of this study was to explore the role of MCM10 in UCEC and construct its overall survival (OS) prediction models. Data from TCGA, GEO, cbioPotal and COSMIC databases and the methods, such as GO, KEGG, GSEA, ssGSEA and PPI, were employed to bioinformatically detect the effects of MCM10 on UCEC. RT‐PCR, Western blot and immunohistochemistry were used to validate the effects of MCM10 on UCEC. Based on Cox regression analysis using the data from TCGA and our clinical data, two OS prediction models for UCEC were established. Finally, the effects of MCM10 on UCEC were detected in vitro. Our study revealed that MCM10 was variated and overexpressed in UCEC tissue and involved in DNA replication, cell cycle, DNA repair and immune microenvironment in UCEC. Moreover, silencing MCM10 significantly inhibited the proliferation of UCEC cells in vitro. Importantly, based on MCM10 expression and clinical features, the OS prediction models were constructed with good accuracy. MCM10 could be an effective treatment target and a prognostic biomarker for UCEC patients. The OS prediction models might help establish the strategies of follow‐up and treatment for UCEC patients. For example, progesterone receptor and oestrogen receptor status have been used to evaluate whether patients can be treated with hormone therapy. However, even in some patients with positive progesterone receptor and oestrogen receptor, single‐agent aromatase inhibitors only achieved 10% response rate.Minichromosome maintenance 10 replication initiation factor (MCM10) gene is a protein‐coding gene located on chromosome region 10p13. MCM10 was first found to involve in the initiation process of DNA replication in yeast.In this study, data from breast cancer, cervical cancer, uterine sarcoma and UCEC in The Cancer Genome Atlas (TCGA) database were used to screen novel biomarkers, and MCM10 was identified to be an effective indicator to predict UCEC prognosis. Subsequently, based on the bioinformatic analysis, we explored the potential function of MCM10 in the development of UCEC and established an overall survival (OS) prediction model for UCEC. Furthermore, in order to validate the effects of MCM10 in UCEC and the reliability of this model, clinical data and pathological sections stained by immunohistochemical staining were employed to construct our clinical data‐based OS prediction model for UCEC. Finally, the potential function of MCM10 in the development of UCEC was verified in vitro.22.12 Fold Change (LogFC) > 3 and adjusted p‐value <0.05 were considered as the cut‐off of DEGs. After taking the intersection of the four DEGs, the top 20% overexpression genes in UCEC were selected to be further screened by Kaplan–Meier analysis in UCEC. Finally, the gene, MCM10, has not been reported to be associated with UCEC were selected in this study.The data sets of breast cancer (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), uterine carcinosarcoma (UCS) and UCEC from TCGA database were employed to screen the biomarkers predicting the prognosis of UCEC. The R package ‘DESeq2’ was used to obtain four differentially expressed genes (DEGs) between tumour and normal tissue  based on the data sets of BRCA, CESC, UCS and UCEC, respectively. The LogThe differential expression data of MCM10 in unpaired and paired samples are RNA‐seq data from TCGA UCEC project and GTEx database. The data were uniformed by the Toil process.2.2p‐value <0.05 were considered as the cut‐off of the DEGs. STRING database was used to visualize the analysis of DEGs,Single‐gene differential analysis and single‐gene correlation analysis of MCM10 in UCEC project based on TCGA database were performed using the DESeq2 package [version 1.26.0] and STAT package [version 3.6.3], respectively.2.3http://www.cbioportal.org/). ‘Uterus’ and ‘Endometrial Carcinoma’ were chosen as the object. A total of 509 endometrial cancer cases from TCGA database was chosen as the sample. The mutation types and frequency of MCM10 in UCEC were obtained from the Catalogue of Somatic Mutations in Cancer (COSMIC) (https://cancer.sanger.ac.uk). Endometrial in ‘tissue distribution’ and ‘mutation distribution’ were chosen.The variation types and frequency of MCMs and MCM10 in UCEC were obtained from the cBioPortal database , Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to further enrich the pathways related to MCM10 in UCEC with the R package ‘clusterProfiler’ and ‘org.Hs.eg.db’. Adjusted p‐value <0.05 was considered as significantly enriched.Gene set enrichment analysis (GSEA) was used to explore potential signalling pathways based on the differential expression analysis (MCM10 high‐expression vs. MCM10 low‐expression samples) in TCGA UCEC project. And c2.cp.v7.2. symbols. gmt was used as the reference gene set. Adjusted 2.5The analysis of immune cell subtypes in TCGA UCEC project was analysed using the GSVA package [version 1.34.0] and single‐sample gene set enrichment analysis (ssGSEA) algorithm.2.6The clinical features of patients with UCEC were obtained from TCGA UCEC project and the Second Hospital of Jilin University, which was used to analyse their correlation with MCM10 expression in UCEC samples. Then, ggplot2 [version 3.3.3] was employed to visualize the results. A receiver operating characteristic (ROC) curve that could demonstrate the ability of MCM10 protein to distinguish endometrial cancer from normal endometrium was drawn to further verify the correlation between MCM10 and UCEC using the pROC package [version 1.17.0.1]. Furthermore, the degree of correlation between the clinical characteristics of UCEC and MCM10 was evaluated by logistics regression, which was visualized by forest plots.2.7The survival data of UCEC patients from TCGA database were used to analyse the correlation between the mRNA expression of various genes  and the prognosis of patients with UCEC using survival package [version 3.2–10] based on Kaplan–Meier method, and the survminer package [version 0.4.9] was used to plot Overall Survival (OS) curves.p‐value <0.1, the significant factors were then included in a multivariate Cox regression model to find the independent risk factors for the OS of UCEC patients. The analysis was performed using the survival package [version 3.2–10], which was visualized by forest plots.Furthermore, univariate Cox regression was used to screen out the risk factors affecting OS from the clinical characteristics and MCM10 expression levels of UCEC patients. After being screened by univariate Cox regression with a cut‐off of Based on the results of multivariate Cox regression, the rms package [version 6.2–0] and survival package [version 3.2–10] were employed to construct the prognostic prediction model predicting 4‐, 6‐ and 8‐year OS, which was visualized by nomograms. Moreover, the calibration plots were drawn using the rms package [version 6.2–0] and survival package [version 3.2–10] to check the accuracy of the prediction models.2.8The present study was approved by the Ethics Committee of the School of Nursing, Jilin University . The patients were informed and agreed to participate in this study. Paraffin‐embedded specimens were collected at the Second Hospital of Jilin University from 119 patients with UCEC and 15 normal controls who were diagnosed between October 2013 and December 2019. The inclusion criteria were as follows: (i) Initially diagnosed with UCEC and treated with standard surgery and/or radiotherapy and/or chemotherapy according to the International Federation of Gynaecology and Obstetrics (FIGO) stage and pathological type of individual patients; (ii) the diagnosis was determined as UCEC by an experienced pathologist; (iii) complete follow‐up data were available. The exclusion criteria were as follows: (i) Individual history of other malignant tumours; (ii) the patients had undergone preoperative radiotherapy, chemotherapy or hormonotherapy; and (iii) secondary uterine tumour. The available clinical/pathological data are shown in Table 2.92. The interference sequences were as follows: shMCM10, 5'‐CGGCGACGGTGAATCTTAT‐3' and shScramble, 5'‐GTATAAGTCAACTGTTGAC‐3'. The lentiviruses used in this study were packaged using the three plasmids packaging system. The lentiviral plasmids (pLKO.1‐shMCM10 or pLKO.1‐Scramble) with two packaging plasmids, including PMD2.G (Fenghui) and psPAX2 (Fenghui) and Lipofectamine™ 3000 transfection reagent (Thermo) were added into HEK‐293 T cells (iCell Bioscience Inc.). After 48 and 72 h, the medium was collected and filtered using 0.22 𝜇m filter. To generate stably transfected cell lines, Ishikawa and HEC‐1‐A cells were seeded into six‐well plates . 1 mL medium containing the above lentiviral was added into each well. The cells were selected in medium containing puromycin (2 μg/mL) and maintained in medium containing puromycin (1 μg/mL). Puromycin selection was continued for 1 week prior to harvesting cells for downstream analysis.The human UCEC cell lines Ishikawa and HEC‐1‐A (iCell Bioscience Inc.) were cultured at 37 °C in a humidified atmosphere with 5% CO2.10Immunohistochemical staining was performed as our previous study.2.11Real‐time PCR was used to detect the transcription levels of MCM10 using the SYBR Green qPCR kit (TransGen) according to the manufacturer's instructions, and 𝛽‐actin was used as an internal control gene. The following primers were used: MCM10 gene forward, 5'‐GGAGAGAACAACTTGCCTATCTG‐3' and reverse, 5'‐AGTAGCGCTCCTGCATCTCA‐3′; 𝛽‐actin gene forward, 5'‐GTGGCCGAGGACTTTGATTG‐3′ and reverse, 5'‐CCTGTAACAACGCATCTCATATT‐3′. The mRNA expression levels were quantified using 2−ΔΔCq method.2.12A total of 15 μg soluble proteins were subjected to each lane of a 4%–20% Precast BIS‐Tris Gel (Absin). Separated proteins were electrophoretically transferred onto polyvinylidene difluoride membranes (Thermo). The membranes were incubated with primary antibodies, including anti‐MCM10  and anti‐GAPDH  and secondary‐HRP antibodies . The protein levels were evaluated under an imaging densitometer (Clinx). The assay was repeated three times independently.2.13Ishikawa, HEC‐1‐A, Ishikawa‐shScramble, HEC‐1‐A‐shScramble, shikawa‐shMCM10 and HEC‐1‐A‐shMCM10 cells were seeded into 96‐well plates (3000 cells/well). Subsequently, 24, 48 and 72 h later, CCK‐8 reagent  was added into each well. The absorbance of each well was measured at 450 nm using a microplate reader .2.14The indicated cells were seeded onto 6‐well plates at a density of 100 cells/well. 10 days later, the formation of typical clone of the cells was observed. The cells were fixed with methanol and stained with 10% Giemsa (Biotopped). The number of visible colonies was counted to evaluate the colony formation ability of cells.2.156 cells/well. Standard immunofluorescence procedures were carried out as a previous study.The indicated cells were seeded on six‐well plates at 2 × 102.16anova) followed by Dunnett's post hoc test, Kruskal–Wallis test or student's t test. Crosstab data were compared by Chi‐squared or Fisher's test. Differences in p < 0.05 were considered statistically significant. All results were repeated three times independently.ssGSEA was used for the algorithm of immune infiltration. Statistical analyses were performed with SPSS 23.0 or R version 3.6.3, the differences among the groups were compared using one‐factor analysis of variance (33.1p < 0.05)  Figure . To the ) Figure  and adja) Figure . Moreove) Figure .3.2The results from the cBioPortal database showed that 26.72% (136/509) of UCEC patients had variation of MCMs Figure , of whic3.3p‐value <0.05) were identified between UCEC samples with high expression and low expression of MCM10  were considered as high‐expression genes, and 2350 genes  were considered as low‐expression genes in the UCEC samples with high MCM10 expression. Twenty related signalling pathways for the 3966 DEGs were enriched and showed by GO and KEGG analysis. Remarkably, we found that the enrichment pathways were mainly associated with humoral immune response, nuclear division, meiotic cell cycle, collagen‐containing extracellular matrix, G protein‐coupled receptor binding, channel activity, enzyme inhibitor activity, passive transmembrane transporter activity and neuroactive ligand–receptor interaction   Figure .3.5r = 0.592, p < 0.001), while negatively correlated with NK CD56bright cells , pDC cells , iDC cells , NK cells  and eosinophils   Figure B,C.3.6p < 0.05). Furthermore, the logistics regression analysis showed that age > 60, serous type, G3 and stage III and IV were risk factors of MCM10 mRNA high expression in UCEC  increased in UCEC tissues as compared with that in normal or adjacent tissues . Interestingly, we found that MCM10 protein expression was positively correlated with MKI67 protein expression   Figure . No sign) Figure . Further) Figure .3.7p < 0.05). Radiation therapy was a prevention factor for the OS of UCEC patients (p < 0.05). Based on the results of univariate Cox regression analysis, we found that age > 60, mixed histological type, stage III, stage IV, PR and MCM10 mRNA expression levels were independent risk factors for the OS of patients with UCEC in TCGA database (p < 0.05)  Figure . As show) Figure .p < 0.05). Based on the results of multivariate Cox regression analysis, we found that mixed histological type, stage III and stage IV, PR and MCM10 protein expression levels were independent risk factors for the OS of patients with UCEC (p < 0.05)  Figure . As show) Figure .3.8p < 0.05). As shown in Figure p < 0.05). Moreover, the colony ability of Ishikawa and HEC‐1‐A cells in shMCM10 groups was significantly (p < 0.05) attenuated compared to the Mock and shScramble groups . It was inspired that pembrolizumab in combination with lenvatinib, a small molecule multikinase inhibitor, was given approval by FDA for advanced or relapsed UCEC patients with MMR‐proficient due to well response rate of this combination therapy.Increasing studies revealed that some small molecule inhibitors could regulate the immune microenvironment of tumour tissue and promote immune‐mediated tumour cell death.In recent years, based on tumour microenvironment‐ and immune‐related genes, several models predicting the prognosis of endometrial cancer have been constructed.The shortcomings of our study are as follows: (i) Although we had validated the expression of MCM10 protein in our clinical samples, the sample size was small, and further validation with larger sample size are still required; (ii) the effects of MCM10 on the development of UCEC were just validated by the experiments in vitro, the experiments in vivo are needed for further validation in the future; (iii) the prediction model was only validated internally in this study and should be further validated externally using clinical specimens and data from other centres in the future.4.1In conclusion, based on public databases and our clinical data, we identified that MCM10 expression was significantly related to the development of UCEC. The function of MCM10 might be mainly involved in DNA replication, cell cycle, DNA repair and tumour immune microenvironment. By integrating TCGA and our clinical data, two novel prognostic models for UCEC were established, which could be used to effectively screen patients who need intensive follow‐up and intervention.Junyu Chen: Conceptualization (supporting); formal analysis (lead); methodology (lead); software (lead); visualization (lead); writing – original draft (lead). Shan Wu: Data curation (supporting); formal analysis ; methodology ; visualization . Junwei Wang: Investigation (supporting); software (lead); supervision (lead); validation (lead); writing – review and editing (supporting). Chunying Han: Investigation (supporting); methodology (supporting); resources ; software ; validation (supporting); writing – review and editing (supporting). Lijing Zhao: Conceptualization (supporting); methodology (supporting); resources ; validation (supporting); writing – review and editing . Kang He: Investigation (supporting); methodology (supporting); resources (supporting); visualization (supporting); writing – review and editing (supporting). Yan Jia: Conceptualization ; funding acquisition ; project administration ; supervision ; writing – review and editing (lead). Manhua Cui: Conceptualization (lead); funding acquisition (lead); project administration (lead).This research was funded by the National Natural Science Foundation of China, grant number: 81772772; Jilin Scientific and Technological Development Program, grant number: YDZJ202201ZYTS580, YDZJ202302CXJD062.The authors declare that they have no competing interests.The patients were informed and agreed to participate in this study.Figure S1:Click here for additional data file.Figure S2:Click here for additional data file.Figure S3:Click here for additional data file.Figure S4:Click here for additional data file.Table S1:Click here for additional data file.Table S2:Click here for additional data file.Table S3:Click here for additional data file.Table S4:Click here for additional data file.Table S5:Click here for additional data file.Table S6:Click here for additional data file.Table S7:Click here for additional data file.Table S8:Click here for additional data file.Table S9:Click here for additional data file.Table S10:Click here for additional data file.Table S11:Click here for additional data file.


There was no statistically significant difference in postoperative Oswestry disability index (ODI) at 1 day , 3 months , or 6 months . Additionally, there were no statistically significant differences in Cobb angle  or anterior vertebral body height  after surgery. Statistically significant differences were found in surgical time , cement infusion volume , and dose of fluoroscopy  between curved and noncurved techniques, especially compared to bilateral PVP. Moreover, cement leakage showed statistically significant difference . Compared with PVP/KP, PCVP is superior for pain relief at short‐term follow‐up. Additionally, PCVP has the advantages of significantly lower surgical time, radiation exposure, bone cement infusion volume, and cement leakage incidence compared to bilateral PVP, while no statistically significant difference is found when compared with unilateral PVP or PKP. In terms of quality of life and radiologic outcomes, the effects of PCVP and PVP/KP are not significantly different. Overall, this meta‐analysis reveals that PCVP was an effective and safe therapy for patients with OVCFs.This systematic review and meta‐analysis is aimed to provide higher quality evidence regarding the efficacy and safety between PCVP and PVP/KP in OVCFs. We searched the Cochrane Library, PubMed, Web of Science, and Embase databases for all randomized controlled trials (RCTs) and observational studies (cohort or case–control studies) that compare PCVP to PVP/KP for OVCFs. The Cochrane Collaboration's Risk of Bias Tool and Newcastle–Ottawa Scale (NOS) were used to evaluate the quality of the RCTs and non‐RCTs, respectively. Meta‐analysis was performed using RevMan 5.4 software. A total of seven articles consisting of 562 patients with 593 diseased vertebral bodies were included. Statistically significant differences were found in the postoperative visual analog scale (VAS) at 1 day (MD = −0.11; 95% CI: [−0.21 to −0.01],  This systematic review and meta‐analysis reveal that PCVP is superior for pain relief at short‐term follow‐up compared with PVP/KP. Additionally, PCVP has the advantages of less surgical time, radiation exposure, bone cement infusion volume, and cement leakage incidence than bilateral PVP. Overall, PCVP is an effective and safe therapy for OVCFs. Along with the trend of population aging, osteoporotic vertebral compression fractures (OVCFs) have become a major global public health problem that threatens the health and quality of life of human beings, especially elderly individuals.Although there are no substantial conclusions on the superiority of cementoplasty over conservative management for OVCFs, it is well‐accepted that conservative treatments are not indicated for every condition and cementoplasty is appropriate in certain circumstances.Indeed, the best minimally invasive procedure for OVCFs is still controversial, with pros and cons.We conducted the current systematic review and meta‐analysis in accordance with the guidelines of the Cochrane handbook for systematic reviews of interventions,S.Y. and Z.Y. independently screened studies. The inclusion criteria were as follows: (1) published randomized controlled trials (RCTs) and observational studies (cohort or case–control studies); (2) patients with OVCFs; (3) intervention was PCVP/KP compared to PVP/KP.The exclusion criteria were as follows: (1) OVCFs caused by pathological reasons including tumor, infection, endocrine system disease, etc.; (2) animal experiments; (3) full‐text article could not be obtained.The data processing was independently performed by two authors (S.Y. and Z.Y.) with Endnote X8 software and disagreements were resolved by consulting the third author (M. HN.). The following data were extracted from each study: (1) descriptive statistics such as author information, publication year, study design, country, data sources, t‐score, sample sizes, and vertebral bodies; (2) intervention in experimental and control groups; (3) the outcome of interest: visual analog scale (VAS), Oswestry disability index (ODI), Cobb angle, anterior vertebral body height, surgical time, injected cement volume, duration of fluoroscopy, cement leakage, or refracture.We used the Cochrane Collaboration's Risk of Bias ToolI2 test and P value. I2 value less than 25% indicated low heterogeneity and a value less than 50% indicated moderate heterogeneity. In such cases, a fixed effects model was adopted. Otherwise, I2 value greater than 50% and P value less than 0.1 indicated significant heterogeneity, and a random effects model was adopted. If the same outcomes were evaluated by different methods, we applied the standardized mean differences (SMDs) of 95% CIs. If there was a significant heterogeneity, a subgroup analysis was performed by removing studies one at a time. p < 0.05 was considered statistically significant.The meta‐analysis was performed using RevMan 5.4 software . The mean difference (MD) of 95% confidence intervals (CIs) was used for continuous outcomes, while dichotomous variables were reported as odds ratios (ORs) and 95% CIs. Statistical heterogeneity was evaluated utilizing the Finally, a total of seven articles including a total of 562 patients with 593 diseased vertebral bodies were included: four RCTsAs shown in Figure p = 0.03, I2 = 0%] but not at 6 months  postoperatively. There may be a significant difference 3 months with a high heterogeneity , thus a further subgroup analyses based on unilateral or bilateral techniques in the control group was performed. However, there was no statistically significant difference regarding unilateral technique , or bilateral technique  at 3 months. A random effects model was utilized due to low to high heterogeneity.Seven trials including 562 subjects reported VAS after surgery at 1 day, three trials including 256 subjects at 3 months, and three trials including 269 subjects at 6 months. As shown in Figure p = 0.10, I2 = 0%], 3 months , and 6 months  postoperatively. A fixed effects model was utilized due to the lack of heterogeneity.Five trials including 380 subjects reported ODI after surgery at 1 day, two trials including 200 subjects at 3 months, and three trials including 269 subjects at 6 months. As shown in Figure p = 0.77, I2 = 0%, Figure Two trials including 168 subjects reported Cobb angle at the final follow up after surgery. As shown in Figure p = 0.92, I2 = 16%, Figure Three trials including 238 subjects evaluated anterior vertebral body height in different measurements at the final follow‐up after surgery. Additionally, no statistically significant difference was found . Due to high heterogeneity, we performed subgroup analyses based on unilateral or bilateral techniques in the control group. Notably, there were substantial changes in heterogeneity when PCVP was compared to unilateral PVP  and compared to bilateral PVP . PCVP had the advantage of less surgical time compared to the bilateral PVP, while there was no difference compared to the unilateral PVP.Seven trials including 562 subjects reported surgical time. As shown in Figure p = 0.02, I2 = 97%]. Due to high heterogeneity, we performed subgroup analyses based on unilateral or bilateral techniques in the control group. There were substantial changes in heterogeneity when PCVP compared to bilateral PVP . In conclusion, PCVP required less cement infusion volume.Six trials including 476 diseased vertebral bodies reported cement infusion volume. As shown in Figure p = 0.0001, I2 = 88%]. Additionally, subgroup analyses were performed. There were substantial changes in heterogeneity when PCVP was compared to bilateral PVP  and compared to unilateral PVP . Based on the results, PCVP required a lower dose of fluoroscopy than bilateral PVP, while there was no difference compared to unilateral PVP.Five trials including 399 subjects reported the dose of fluoroscopy. As shown in Figure p < 0.0001, I2 = 0%].Seven trials including 562 subjects reported cement leakage. As shown in Figure p = 0.43, I2 = 47%]. A fixed effects model was utilized due to low heterogeneity. Therefore, PCVP had the advantage of a low risk of cement leakage compared to the noncurved technique.Two trials including 174 subjects reported refracture. There was no statistically significant difference between curved and noncurved techniques [OR = 0.58 (95% CI 0.15–2.23), PCVP showed superior short‐term pain relief compared with conventional cementoplasty. In the present study, statistically significant differences were found in postoperative VAS at 1 day and 3 months, but not at 6 months. As PVP/KP has been widely used, numerous studies have reported the desired analgesic efficacy of PVP/KP maintained for 1 day,Notably, PCVP showed similar results to PVP/KP regarding ODI, Cobb angle, and anterior vertebral body height at short‐ and mid‐term follow‐up. A multicenter RCT confirmed the long‐term improvement of PKP over conservative treatment with respect to quality of life and kyphotic correction.In view of the similar or better clinical outcomes, PCVP was preferred for safety reasons. According to the results, PCVP had the advantage of less surgical time than bilateral PVP, which is more suitable for elderly patients reluctant to undergo prolonged prone lying.Regarding complications, PCVP had a lower incidence of cement leakage. Cement leakage could be a serious complication,To the best of our knowledge, this was the first meta‐analysis to evaluate the effectiveness of PCVP versus PVP/KP on OVCFs. However, the study had some limitations. First, the PCVP methods varied among studies, which may increase the risk of heterogeneity. Second, most studies included OVCFs at a single level due to the complex situation in multiple OVCFs. The combination of several techniques may be an alternative under certain circumstances. Third, the number of studies included was limited, partly due to the initial application stage of the novel technique. Therefore, more RCTs with comprehensive and long‐term clinical and imaging results are needed in the future to better determine efficacy and facilitate standardized treatment regimens.Compared with PVP/KP, PCVP is superior for pain relief at short‐term follow‐up. Additionally, it has the advantages of significantly lower surgical time, radiation exposure, and bone cement infusion volume and cement leakage incidence than bilateral PVP, while no statistically significant difference is found when compared with unilateral PVP or PKP. In terms of quality of life and radiologic outcomes, the effects of PCVP and PVP/KP are not significantly different. Overall, this meta‐analysis reveals that PCVP was an effective and safe therapy for patients with OVCFs.The authors declare that they have no conflict of interest.This study is a meta‐analysis and does not require ethical approval and consent to participate.S.Y. and Z.Z.H. conceived and designed the study. S.Y. and Z.Y. performed the literature search and collected the data. T.M.S. and M.H.N. contributed to the critical revision of the manuscript. All authors were involved in writing the manuscript. All authors read and approved the final manuscript.


We launched a single‐arm phase II study to determine the efficacy and cost‐effectiveness of percutaneous endoscopic gastrostomy (PEG) before concurrent chemoradiotherapy (CCRT) in patients with esophageal squamous cell carcinoma (ESCC).Eligible patients received pretreatment PEG and enteral nutrition during CCRT. The primary outcome was the change of weight during CCRT. The secondary outcome included nutrition status, loco‐regional objective response rate (ORR), loco‐regional progression‐free survival (LRFS), overall survival (OS), and toxicities. A 3‐state Markov model was applied for cost‐effectiveness analysis. Eligible patients were matched and compared with those who had nasogastric tube feeding (NTF) or oral nutritional supplements (ONS).p = 0.001). The PEG group showed higher loco‐regional ORR (p = 0.036) and longer 1‐year LRFS (p = 0.030). In cost analysis, the PEG group showed an incremental cost‐effectiveness ratio of $3457.65 per quality‐adjusted life‐years (QALY) compared with the ONS group with a probability of cost‐effectiveness of 77.7% at the $10,000 per QALY willingness‐to‐pay threshold.Sixty‐three eligible patients received pretreatment PEG‐based CCRT. The mean change of weight during CCRT was −1.4% , and after CCRT, 28.6% of patients gained weight and 98.4% had normal albumin levels. The loco‐regional ORR and 1‐year LRFS were 98.4% and 88.3%. The incidence of grade ≥3 esophagitis was 14.3%. After matching, another 63 patients were included in the NTF group and 63 in the ONS group. More patients gained weight after CCRT in the PEG group (Pretreatment PEG is associated with better nutritional status and treatment outcome in ESCC patients treated with CCRT compared with ONS and NTF. Pretreatment of PEG can be cost‐effective because of its significant clinical benefits. Study subjects were recruited from May 15, 2018 to March 19, 2020. Eligibility criteria included the following: (1) 18–75 years of age, (2) histologically proven esophageal squamous cell carcinoma, (3) inoperable stage II‐IVA disease based on the TNM staging system proposed by the Union for International Cancer Control (UICC) 2002, (4) Eastern Cooperative Oncology Group (ECOG) performance status (PS) 0–1, (5) Patient‐Generated Subjective Global Assessment (PG‐SGA) grade of A‐B, and (6) estimated life expectancy is at least 6 months. The main exclusion criteria included: (1) contraindications for percutaneous endoscopic gastrostomy; (2) contraindication for chemotherapy or radiotherapy; (3) severe gastrointestinal dysfunction or enteral nutrition intolerance and (4) severe vomiting, bowel obstruction, or gastrointestinal bleeding. This study was approved by the institutional review board. All patients signed a written informed consent form.This single‐arm phase II trial was conducted at Sun Yat‐sen University Cancer Center . The tumor response was evaluated 2 months after the CCRT based on endoscopy and biopsy (if necessary), contrast‐enhanced computed tomography (CT) of the neck, chest, and upper abdomen, and chest magnetic resonance imaging (MRI). After the tumor response evaluation, a percutaneous endoscopic gastrostomy tube could be removed for patients without deep ulcers or residual tumors in their esophagus. Patients then received regular follow‐ups thereafter.2.3The primary endpoint was the change of weight during CCRT, which was defined as the percentage of weight loss from baseline till the end of CCRT. The secondary endpoints were nutrition status, measured by the change of albumin, hemoglobin, and CRP level during CCRT; loco‐regional objective response rate (ORR) was evaluated by tumor in the esophagus and mediastinal nodes, excluding distant metastasis; loco‐regional progression‐free survival (LRFS), defined as the time from enrollment to the date of loco‐regional disease progression or death from any cause or censored at the last date of follow‐up; overall survival (OS), defined as the time from enrollment to death or censored at the last date of the follow‐up; ≥3‐grade acute esophagitis, pneumonia, and hematological toxicity. Nutrition status was evaluated at the end of CCRT. ORR was assessed 2 months after CCRT. Acute toxicities were evaluated from the start till 3 months after CCRT.2.4Patients with oral nutrition support (ONS group) and nasogastric tube feeding (TNF group) were included in other two clinical trials conducted in our center during the same period (NCT02403531 and NCT02969473). The matching was based on 1:1:1 matching within a prespecified caliper width without replacement .2.5A Markov‐based state transition model was established to simulate the clinical status of patients with inoperable ESCC Figure . The basCost included the following expenditure: radiotherapy, chemotherapy, nutrition support cost, treatment of major AEs costs, and hospitalization cost. Each price of these costs is based on our center. To compare the costs of different enteral nutrition supplement groups, healthcare costs during the initial 3 months and 6 months after the start of radiotherapy were analyzed. All costs were adjusted to US dollars with an exchange rate of $1 = ¥6.37 .The cost‐effectiveness analysis followed the guidelines of the Second Panel on Cost‐Effectiveness in Health and Medicine.One‐way sensitivity analysis was performed to estimate the impact of different model parameters on the ICER. A probabilistic sensitivity analysis was performed to assess the uncertainty of the ICER estimate by using Monte Carlo simulation from 10,000 samples at different hypothetical willingness to pay (WTP) thresholds. The outcomes were reported as cost‐effectiveness probability for $10,000 per QALY and $50,000 per QALY as well as cost‐effectiveness acceptability curves. We applied international standards to define a strategy as “cost‐effective” if its ICER was below three times the gross domestic product (GDP) per capita in China .2.6The primary endpoint of this trial was the change of weight during CCRT. We assumed that the change of weight could be reduced from −5.0% according to previous studiesp value of 0.05 or less was considered statistically significant. Descriptive statistics and survival analysis were performed by SPSS 26.0. Propensity score analysis was performed using the SAS statistical software version 9.1 (SAS Institute). We construct a 3‐state Markov model to analyze the cost‐effectiveness using Treeage software .A descriptive statistical analysis of baseline characterization and toxicity was performed. For all outcome measures, differences among groups were tested using one‐way ANOVA or Chi‐square test. Kaplan–Meier method was used to estimate the survival rates. We report the corresponding symmetric 95% confidence intervals (CIs). 33.1From May 15, 2018 to March 19, 2020, 87 patients were assessed and 63 patients were enrolled in this study as the PEG group. Baseline characteristics are shown in Table 3.2n = 9), grade ≥3 hematological toxicity (n = 3), and heart failure (n = 1). Hence, 3 of 63 (4.8%) patients had a dose reduction of S‐1 due to hematological toxicities.Of the 63 patients, 61 (96.8%) patients completed the full‐dose radiotherapy, and two patients failed to complete radiotherapy due to persisted grade of ≥2 esophagitis. Radiotherapy interruption occurred in 13 patients due to grade ≥3 esophagitis  had gastrostomy feeding tube removal at the first or second follow‐up, and 5 patients (7.94%) retained their tube in the long term. The median duration of gastrostomy tube retention was 4.0 months .3.3As shown in Table 3.4Two months after CCRT, there were 50 patients evaluated with loco‐regional complete remission (CR), and 12 with loco‐regional partial remission (PR)  months. The estimated 1‐year LRFS rate and 1‐year OS were 88.3% and 88.6%, respectively.3.5Common acute toxicities of patients treated with pretreatment PEG were also presented in Table 3.6p < 0.001) and higher radiation fraction size . The mean overall treatment time (OTT) was shorter in the PEG group .Process flow diagram of this study is shown in Figure p = 0.157). Thirty (47.6%) patients in the NTF group and 25 (39.7%) patients in the ONS group experienced radiotherapy interruption, while this occurred in 13 (20.6%) patients in the PEG group (p = 0.005).During the whole treatment, more patients in the PEG group tended to complete the full‐dose radiotherapy  and −3.0%  in the ONS group (p = 0.046). Weight gain after CCRT occurred in 28.6% of the patients in the PEG group, whereas 12.7% in the NTF group and 11.1% in the ONS group (p = 0.001). Approximately, 98.4% of patients had ≥35 g/L albumin level after CCRT in the PEG group, compared with 88.9% in the NTF group and 81.0% in the ONS group (p = 0.006), and 39.7% of patients had ≥15 mg/L CRP after CCRT in the PEG group, compared with 57.1% in the NTF group and 60.3% in the ONS group (p = 0.044). After CCRT, 11 (17.5%) patients in the PEG group had LY# ≥1.0*10E9/L, whereas only 7 (11.1%) in the NTF group and 3 (4.8%) in the ONS group (p = 0.076).As shown in Table p = 0.036). As shown in Table p = 0.030). The 1‐year OS was 88.6% in the PEG group, 83.1% in the NTF group, and 81.2% in the ONS group (p = 0.576).Four to eight weeks after the end of radiotherapy, the loco‐regional disease was evaluated for the groups Table . Approxip = 0.045). The incidence of grade ≥3 anemia was higher in the NTF group . Incidence of grade ≥3 lymphopenia tended to be higher in the PEG group . No significant difference in other hematologic toxicities among the three groups was observed.Major treatment‐related toxicities in three groups were listed in Table 3.7p = 0.056). The average medical costs of the radiotherapy were calculated at $10,086.04 for the PEG group, $8519.56 for the NTF group, and $8377.22 for the ONS group (p < 0.001). The enteral nutrition support cost was higher in the PEG group (p = 0.001). Total costs in 3 months and 6 months showed no statistically significant differences among the 3 enteral nutrition support groups. The PEG group had a significantly shorter length of hospital stay during CCRT .As detailed in Table The 3‐state Markov model is shown in Figure In one‐way analysis, the ICER was sensitive to the treatment cost of radiotherapy, routine follow‐up, and nutrition support cost and was also sensitive to the probability of mortality, relapse, and utility after treatment. The model variables in the order of their influence on the ICER were presented in Figure 4p = 0.036), longer 1‐year LRFS . The PEG group had a significantly shorter length of hospital stay during CCRT  and appeared to be cost‐effective due to significant survival benefits.Pretreatment PEG‐based CCRT showed promising treatment response and tolerable CCRT‐induced toxicities in unresectable locally advanced ESCC patients. The loco‐regional ORR and 1‐year LRFS were 98.4% and 88.3%. The incidence of grade ≥3 esophagitis was 14.3% (9/63) and no patient experienced grade ≥3 pneumonitis. In the current study, we also compared the efficacies, toxicities, nutrition status, and costs of three different enteral support groups. PEG group showed higher loco‐regional ORR  when treated with definitive CCRT. The lower incidence of severe CCRT‐induced esophagitis in the PEG group suggested that adequate enteral nutrition promotes the repair of the esophageal mucosa. Tube feeding could also reduce the pain caused by oral feeding and the incidence of malnutrition. More patients in the PEG group gained weight after CCRT due to improved efficacy and reduced symptoms . In the current study, the daily energy and protein requirements of patients were 25–30 kcal/kg and 1.2–1.5 g of protein/kg, respectively. If severe protein depletion occurs, it is necessary to increase doses up to 2.0 g/kg/day to avoid the loss of lean body mass.Our previous results found that the incidence of grade ≥3 radiation esophagitis including massive bleeding and perforation was significantly lower in ESCC patients with PEG (p = 0.006) and had less incidence of grade ≥3 anemia  during treatment. In addition, 11 (17.5%) patients in the PEG group had lymphocyte ≥1.0*10E9/L after CCRT, compared with 7 (11.1%) patients in the NTF group and 3 (4.8%) patients in the ONS group (p = 0.076). This group of patients is more likely to benefit from subsequent immunotherapy.Malnutrition predicts poor prognosis for esophageal cancer patients treated with chemotherapy or/and radiotherapy.n = 6, 9.5%), including peristomal site infection , tube blockage , and tube dislodgement . The following measures should be taken to reduce the risk of PEG‐related complicationsSix patients in the PEG group developed complications (p = 0.056). As the costs of CCRT and enteral nutrition support were higher, the lower total treatment costs in the PEG group were probably related to the reduction in antibiotics and emergency treatment . Compared with the ONS group, NTF and PEG groups showed higher costs for nutrition support, which indicated more care for nutritional status. Besides, with the lower incidence of treatment‐related AEs and improved quality of enteral nutrition services, the length of hospitalization stay was reduced by half with 11.3 days in the PEG group. The shortened duration of CCRT not only contributed to the reduction of treatment costs but also minimized the length of hospitalization and long‐distance travel during the COVID‐19 epidemic. Moreover, the economic preferences for the PEG should be interpreted cautiously in the setting of different treatment approaches and economic environments.We also found that the total costs of the PEG group from diagnosis till 6 months after CCRT were slightly lower among 3 groups ; formal analysis (lead); resources (lead); software (lead); writing – original draft (lead). PengXin Zhang: Data curation (lead); formal analysis (lead); resources (lead); validation ; writing – original draft (lead); writing – review and editing . XinMin Xie: Data curation ; formal analysis ; investigation ; project administration ; software . Bo Qiu: Data curation ; investigation ; project administration ; supervision ; writing – review and editing . YuJia Zhu: Methodology ; project administration ; resources . Lei Zhao: Methodology ; project administration ; resources . Mian Xi: Formal analysis ; project administration ; resources . YingJia Wu: Funding acquisition ; project administration ; resources . SuPing Guo: Project administration ; resources . JinYu Guo: Project administration . FangJie Liu: Project administration ; resources . DaQuan Wang: Project administration ; resources ; software . NaiBin Chen: Investigation ; project administration ; resources ; software . QianWen He: Investigation ; project administration . YongHong Hu: Investigation . MengZhong Liu: Investigation . ZhaoXia Ding: Conceptualization ; investigation ; methodology ; supervision . Hui Liu: Conceptualization (lead); data curation (lead); methodology (lead); supervision (lead); writing – review and editing (lead).The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Figure S1.Click here for additional data file.


To evaluate clinical outcomes after endometrial receptivity analysis (ERA).This was a multicenter, retrospective cohort study involving 861 women who underwent ERA testing at certified fertility clinics in Japan, and who received subsequent personalized blastocyst embryo transfers (ET) between 2018 and 2020. Clinical outcomes, including pregnancies, miscarriages, and live births, were evaluated according to receptivity status for ERA.Mean patient age was 37.7 years (SD = 4.0), and the median number of previous ETs was 2 . 41.0% (353/861) of patients were non‐receptive for ERA testing. Clinical pregnancy, miscarriage, and live birth rates for personalized blastocyst ET were 44.5% (226/508), 26.1% (59/226), and 26.8% (136/508) for receptive patients, and 43.1% (152/353), 28.3% (43/152), and 28.9% (102/353) for non‐receptive patients, all statistically nonsignificant. Multiple logistic regression demonstrated similar nonsignificant associations between receptivity and clinical outcomes. Greater patient age, smoking, and longer duration of infertility were significantly and negatively associated with receptivity, whereas a history of delivery was positively associated and statistically significant.Clinical outcomes after ERA testing were similar between receptive and non‐receptive patients. Further prospective study including an appropriate comparison group are warranted to evaluate the efficacy of ERA testing. This paper discusses the effectiveness of ERA testing based on ERA results and clinical outcomes. A retrospective study with the largest number of patients has been conducted and is expected to provide useful findings. We asked 11 ART facilities participating in JISART for clinical information about all cases without submucosal uterine myoma or hydrosalpinx, who received ERA between January 2018 and December 2020.Inclusion criteria for analysis were that (1) ERA was conducted during a hormone replacement cycle (HRC), (2) Subsequent personalized blastocyst ET was conducted under HRC after ERA. All participating ART facilities offered ERA testing for patients with RIF.2.2Patient characteristics including age at the time of both oocyte retrieval and ET, body mass index (BMI), smoking status, infertility duration, pregnancy and delivery history were recorded. Additional clinical information including serum anti‐Müllerian hormone (AMH) level, infertility diagnoses, and numbers of previous ETs were also assessed.2.3n = 625), while one facility took them at 108 h (n = 74), another at 118 h (n = 11) and a third facility took them at 123 h (n = 151). Biopsied endometrial samples were put into cryotubes containing 1.5 mL RNA and shaken for a few seconds. Samples were kept at 4°C for 4 h and shipped at room temperature to Igenomix Japan for ERA analysis. No patients received ERA testing multiple times during the study period. Further, there were no potential conflicts of interest between those conducting this research and the company performing ERA testing.From Day 3 of the menstrual cycle, a transdermal estradiol patch  was used for 10–14 days, and oral conjugated estrogen tablets  were added if necessary. If endometrium thickness was ≥7 mm with an adequate serum estradiol level, either 300‐mg vaginal progesterone suppositories  three times daily or chlormadinone acetate  (12 mg per day) were initiated. If serum progesterone levels were >1 ng/mL at the time of progesterone initiation, that cycle was canceled. Endometrial biopsy was performed from the uterine fundus using a Pipet Curet  as described earlier.ERA test results enabled classification of each patient's WOI as “receptive” or “non‐receptive.” Non‐receptive patients were further classified as “pre‐receptive,” “early‐receptive,” “late receptive,” or “post‐receptive,” meaning that the status at the time of the biopsy was 24 h earlier, 12 h earlier, 12 h later, or 24 h later than the patient's individual WOI, respectively. Therefore, in a subsequent cycle, personalized vitrified‐warmed blastocyst transfer ET was performed according to individual patient timing for WOI, based on results of the ERA test, at the time that the result was non‐receptive.2.4We investigated clinical outcomes of clinical pregnancies, miscarriages, ongoing pregnancies, and live births. Clinical pregnancy was defined as confirmation of a gestational sac in utero. Miscarriage was defined as complete expulsion of products of conception before 22 weeks of gestation. Ongoing pregnancy was defined as a pregnancy that continued beyond 12 weeks of gestation.2.5t‐tests. Second, clinical outcomes of the first personalized ET following ERA were evaluated in all patients (n = 861), patients with RIF, defined as patients without pregnancy after two ETs (n = 627), and ETs receiving preimplantation genetic testing for aneuploidy (PGT‐A) (n = 69), using a Chi‐squared test. Third, to evaluate factors associated with receptivity, we conducted multiple logistic regression and calculated odds ratios (ORs) and 95% confidence intervals (95% CIs) for receptivity. Variable selection for multivariable analysis was based on forward stepwise variable selection methods, considering effects of confounding factors. Finally, in order to evaluate associations between receptive status and clinical outcomes after ERA testing, we also investigated crude and adjusted ORs of receptive status for clinical outcomes among patients with RIF. Variables that demonstrated significant associations with receptivity, as well as treatment factors that demonstrated significant differences between receptive status, that is, assisted hatching, numbers of embryos transferred, and endometrial thickness at ET, were included in the adjusted analysis. All analyses were conducted using the Stata MP statistical package, version 17.0 . A two‐tailed p‐value of <0.05 was considered statistically significant.First, we evaluated whether patient characteristics, including clinical information for personalized ET, differed between receptive and non‐receptive groups for ERA testing, using Chi‐squared or Student's 3A sample flow chart is shown in Figure p < 0.001). Non‐receptive patients were more likely to have been smokers and to have had longer infertility than receptive patients (p < 0.05). Proportions of infertility diagnoses and time from progesterone initiation to ERA testing were similar in both groups.Overall, 353 patients 41.0%) were non‐receptive (Table .0% were p < 0.01), while proportions of late receptive patients decreased from 6.4% (3/47) to 3.0% (7/232)  at age 30 or younger, 32.0% (62/194) at age 31–35, 39.4% (153/388) at age 36–40, and 49.1% (114/232) at age 41 or older, with a significant increasing trend (p < 0.05) (Table n = 627) and ETs following PGT‐A (n = 69).Compared with patients with receptive status, non‐receptive patients were more likely to have received assisted hatching and single‐embryo transfer, while endometrial thickness at ET was significantly greater than in patients with receptive status (5) Table . Clinica5) Table , which wIn the crude analysis, older patients at ETs and those with longer duration of infertility had significantly lower odds for receptivity. In the multivariable model, significant associations between those variables and receptivity remained Table . Further4In this multicenter, cross‐sectional study at certified fertility clinics in Japan, 41.0% of patients (353/861) were non‐receptive. Clinical pregnancy, miscarriage, ongoing pregnancy, and live birth rates for first personalized blastocyst ET after ERA testing were similar between receptive and non‐receptive patients. Multiple logistic regression demonstrated that advanced age, smoking, and longer duration of infertility were negatively associated with receptivity, whereas a history of delivery was positively associated. Among patients with RIF, there were no significant associations between receptivity and clinical outcomes. To the best of our knowledge, this is the largest study to investigate clinical outcomes after ERA, as well as factors associated with endometrial receptivity.Clinical pregnancy, miscarriage, ongoing and live birth rates for the first personalized ET were comparable for receptive and non‐receptive patients Table . Those an = 255) and donor transfers (n = 319). They found that implantation, pregnancy, and clinical pregnancy rates were lower in patients undergoing personalized ET than ETs unguided by ERA. On the other hand, Liu et al. reported meta‐analyses, including observational studies about ERA testing efficacy. They reported that the ongoing pregnancy rate/live birth rate for those who followed personalized ET with ERA was somewhat higher (but nonsignificant) than for patients undergoing routine ET without ERA testing, among infertile patients with good prognoses . Further, among patients with RIF, the ongoing pregnancy rate/live birth rate for personalized ET among those who were non‐receptive, increased to the level of receptive patients undergoing ETs .Because we did not compare the outcomes between patients with or without ERA testing, whether ERA has a positive impact on ART success is unknown. Previous reports on ERA demonstrated controversial results for the effect of ERA.fers n = 19. They p = 0.04).Although our analysis did not show significant associations between the number of previous ETs and receptivity in either crude or adjusted analysis, several studies suggested a link between the number of implantation failures and proportions of receptive and non‐receptive patients. Mahajan et al. reported that 186 patients were divided into two groups based on the number of implantation failures. Among Group I persons who failed only one IVF cycle, 15.1% were non‐receptive, while among Group II patients, who failed three IVF cycles, 27.5% were non‐receptive  and the Helsinki Declaration of 1964 and its later amendments.This article does not contain any studies with animal subjects performed by any of the authors.This study was approved by the ethics committee of Kyono ART clinic Takanawa, study reference number 4905–210906.


Most intracranial lipomas are asymptomatic, but headache is the most common symptom. The pounding score is sometimes high. Therefore, it is necessary to monitor imaging findings in parallel with the treatment of migraine.  Head CT. Upper row: (A) is a lipoma in the right lateral ventricle and (B) in the third ventricle. (white arrow). Lower row: It can be confirmed that both A and B are not air under lung field conditions. (black circle). A 29‐year‐old woman presented to the emergency department with a 2‐month‐old headache. Her headache was a unilateral throbbing headache like she had never experienced before. Her headache lasted more than 4 h and was accompanied by vomiting. Otherwise, she had no abnormal neurological findings. She has a history of obsessive‐compulsive disorder. She is on regular oral paroxetine hydrochloride and cloxazolam. She gained 30 kg weight in 4 years. So far, she has not seen a doctor because of her headache, although she has acknowledged it many times. She had blood pressure of 120/80 mmHg, pulse of 60/beat, body temperature of 35.0°C, pupil of 5 mm/5 mm, and bilateral light reflex. Her Glasgow Coma Scale was 15 with no neck stiffness. Her blood tests showed no abnormalities. She underwent a head CT to rule out subarachnoid hemorrhage. Her head CT showed no intracranial hemorrhagic lesions. However, she had low‐density structures in the right lateral ventricle and third ventricles. CT values ranged from −20 to −80. When the head CT was set to the condition of the lung field, it was visually confirmed that it was not air Figure . As a reYudai Aikawa: Writing – original draft; writing – review and editing. Takanobu Sato: Writing – review and editing. Ryo Ichibayashi: Supervision; writing – review and editing.The author(s) received no financial support for this article's research, authorship, and/or publication.The authors have no conflict of interest to disclose.Written informed consent was obtained from the patient to publish this report by the journal's patient consent policy.