A Personalized Dose-Finding Algorithm Based on Adaptive Gaussian Process Regression.

Dose-finding studies play a crucial role in drug development by identifying the optimal dose(s) for later studies while considering tolerability. This not only saves time and effort in proceeding with Phase III trials but also improves efficacy. In an era of precision medicine, it is not ideal to assume patient homogeneity in dose-finding studies as patients may respond differently to the drug. To address this, we propose a personalized dose-finding algorithm that assigns patients to individualized optimal biological doses. Our design follows a two-stage approach. Initially, patients are enrolled under broad eligibility criteria. Based on the Stage 1 data, we fit a regression model of toxicity and efficacy outcomes on dose and biomarkers to characterize treatment-sensitive patients. In the second stage, we restrict the trial population to sensitive patients, apply a personalized dose allocation algorithm, and choose the recommended dose at the end of the trial. Simulation study shows that the proposed design reliably enriches the trial population, minimizes the number of failures, and yields superior operating characteristics compared to several existing dose-finding designs in terms of both the percentage of correct selection and the number of patients treated at target dose(s).

Bayesian inference for multivariate probit model with latent envelope.

The response envelope model proposed by Cook et al. (2010) is an efficient method to estimate the regression coefficient under the context of the multivariate linear regression model. It improves estimation efficiency by identifying material and immaterial parts of responses and removing the immaterial variation. The response envelope model has been investigated only for continuous response variables. In this paper, we propose the multivariate probit model with latent envelope, in short, the probit envelope model, as a response envelope model for multivariate binary response variables. The probit envelope model takes into account relations between Gaussian latent variables of the multivariate probit model by using the idea of the response envelope model. We address the identifiability of the probit envelope model by employing the essential identifiability concept and suggest a Bayesian method for the parameter estimation. We illustrate the probit envelope model via simulation studies and real-data analysis. The simulation studies show that the probit envelope model has the potential to gain efficiency in estimation compared to the multivariate probit model. The real data analysis shows that the probit envelope model is useful for multi-label classification.

Spatial N-glycomics of the normal breast microenvironment reveals fucosylated and high-mannose N-glycan signatures related to BI-RADS density and ancestry.

Higher breast cancer mortality rates continue to disproportionally affect black women (BW) compared to white women (WW). This disparity is largely due to differences in tumor aggressiveness that can be related to distinct ancestry-associated breast tumor microenvironments (TMEs). Yet, characterization of the normal microenvironment (NME) in breast tissue and how they associate with breast cancer risk factors remains unknown. N-glycans, a glucose metabolism-linked post-translational modification, has not been characterized in normal breast tissue. We hypothesized that normal female breast tissue with distinct Breast Imaging and Reporting Data Systems (BI-RADS) categories have unique microenvironments based on N-glycan signatures that varies with genetic ancestries. Profiles of N-glycans were characterized in normal breast tissue from BW (n = 20) and WW (n = 20) at risk for breast cancer using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). A total of 176 N-glycans (32 core-fucosylated and 144 noncore-fucosylated) were identified in the NME. We found that certain core-fucosylated, outer-arm fucosylated and high-mannose N-glycan structures had specific intensity patterns and histological distributions in the breast NME dependent on BI-RADS densities and ancestry. Normal breast tissue from BW, and not WW, with heterogeneously dense breast densities followed high-mannose patterns as seen in invasive ductal and lobular carcinomas. Lastly, lifestyles factors (e.g. age, menopausal status, Gail score, BMI, BI-RADS) differentially associated with fucosylated and high-mannose N-glycans based on ancestry. This study aims to decipher the molecular signatures in the breast NME from distinct ancestries towards improving the overall disparities in breast cancer burden.

Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics.

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

Effect of complicated, untreated and uncontrolled diabetes and pre-diabetes on treatment outcome among patients with pulmonary tuberculosis.

BACKGROUND AND OBJECTIVE: Patients with tuberculosis and diabetes have a higher risk of unfavourable anti-tuberculosis treatment outcomes. In the present study, we aimed to evaluate the effects of various diabetes statuses on the outcomes of patients with pulmonary tuberculosis. METHODS: Among the patients with pulmonary tuberculosis enrolled in the Korea Tuberculosis Cohort (KTBC) registry and the multicentre prospective cohort study of pulmonary tuberculosis (COSMOTB), those with diabetes and complicated diabetes were identified. The primary and secondary outcomes were unfavourable outcomes and mortality, respectively. The effect of diabetes and complicated diabetes on the outcomes was assessed using multivariable logistic regression analysis. Using COSMOTB, subgroup analyses were performed to assess the association between various diabetes statuses and outcomes. RESULTS: In the KTBC, diabetes (adjusted odds ratio [aOR] = 1.93, 95% CI = 1.64-2.26) and complicated diabetes (aOR = 1.96, 95% CI = 1.67-2.30) were significantly associated with unfavourable outcomes, consistent with the COSMOTB data analysis. Based on subgroup analysis, untreated diabetes at baseline was an independent risk factor for unfavourable outcomes (aOR = 2.72, 95% CI = 1.26-5.61). Prediabetes and uncontrolled diabetes increased unfavourable outcomes and mortality without statistical significance. CONCLUSION: Untreated and complicated diabetes at the time of tuberculosis diagnosis increases the risk of unfavourable outcomes and mortality.

The Matrix Stiffness Coordinates the Cell Proliferation and PD-L1 Expression via YAP in Lung Adenocarcinoma.

The extracellular matrix (ECM) exerts physiological activity, facilitates cell-to-cell communication, promotes cell proliferation and metastasis, and provides mechanical support for tumor cells. The development of solid tumors is often associated with increased stiffness. A stiff ECM promotes mechanotransduction, and the predominant transcription factors implicated in this phenomenon are YAP/TAZ, ß-catenin, and NF-κB. In this study, we aimed to investigate whether YAP is a critical mediator linking matrix stiffness and PD-L1 in lung adenocarcinoma. We confirmed that YAP, PD-L1, and Ki-67, a marker of cell proliferation, increase as the matrix stiffness increases in vitro using the lung adenocarcinoma cell lines PC9 and HCC827 cells. The knockdown of YAP decreased the expression of PD-L1 and Ki-67, and conversely, the overexpression of YAP increased the expression of PD-L1 and K-67 in a stiff-matrix environment (20.0 kPa). Additionally, lung cancer cells were cultured in a 3D environment, which provides a more physiologically relevant setting, and compared to the results obtained from 2D culture. Similar to the findings in 2D culture, it was confirmed that YAP influenced the expression of PD-L1 and K-67 in the 3D culture experiment. Our results suggest that matrix stiffness controls PD-L1 expression via YAP activation, ultimately contributing to cell proliferation.

Immune Evasion of G-CSF and GM-CSF in Lung Cancer.

Tumor immune evasion is a complex process that involves various mechanisms, such as antigen recognition restriction, immune system suppression, and T cell exhaustion. The tumor microenvironment contains various immune cells involved in immune evasion. Recent studies have demonstrated that granulocyte colony-stimulating factor (G-CSF) and granulocyte-macrophage colony-stimulating factor (GM-CSF) induce immune evasion in lung cancer by modulating neutrophils and myeloid-derived suppressor cells. Here we describe the origin and function of G-CSF and GM-CSF, particularly their role in immune evasion in lung cancer. In addition, their effects on programmed death-ligand 1 expression and clinical implications are discussed.

Data-driven monitoring for phase II clinical trial designs based on percentile event time test.

The goal of phase II clinical trials is to evaluate the therapeutic efficacy of a new drug. Some investigators want to use the time-to-event endpoint as the primary endpoint of the phase II study to see the improvement of the therapeutic efficacy of a new drug in median survival time. Recently, median event time test (METT) has been proposed to provide a simple and straightforward rule which compares the observed median survival time with the prespecified threshold. However, median survival time would not be observed during the trial if the drug performs well and indeed cures most patients or if the accrual rate is so fast. To address the issues in clinical practice, we first propose a percentile event time test (PETT), which generalizes METT to any percentile of the survival time, and develop data-driven monitoring for phase II clinical trial designs based on PETT. We evaluate the performance of the method through simulations and illustrate the proposed method with a trial example.

Sample size determination and evaluation for two-stage adaptive designs of single arm clinical trials based on median event time test.

Clinical trials play a critical role in drug development which involves a series of phases and requires a significant amount of time and effort. Efficient clinical trial designs are necessary to investigate a new drug. Investigators strongly desire to use the time-to-event endpoint as the primary endpoint for Phase II studies, which evaluates the therapeutic efficacy of the new drug, with the hypothesis that the new drug improves the median survival time. The one-sample log-rank test has been used for single-arm Phase II trials, but it generally requires more samples. Recently, the median event time test was proposed to provide a simple, straightforward decision rule, which compares the observed median survival time for the new drug with the threshold, which is determined through the numerical search. We improve the computation of the method for the two-stage design of single-arm clinical trials based on the median event time test. By utilizing the large sample theory of order statistics, we provide the explicit formulas to calculate the sample size for the first and second stages and propose the testing procedure. The performance of the proposed method is evaluated through simulations and a trial example.

Neutrophil-to-eosinophil ratio as a biomarker for clinical outcomes in advanced stage melanoma patients treated with anti-PD-1 therapy.

Neutrophil-to-lymphocyte ratios (NLR) and eosinophil counts are associated with improved survival in melanoma patients treated with immune checkpoint inhibitors, but no study has investigated neutrophil-to-eosinophil ratios (NER) as a predictive indicator in this population. In this retrospective study evaluating anti-PD-1 treated patients with advanced melanoma, progression-free survival (PFS), overall survival (OS), objective response rates (ORR), and risk of high-grade (grade ≥3) immune-related adverse events (irAEs) were compared between groups defined by median pretreatment NLR and NER as well as median NLR and NER at 1-month post-treatment. Lower baseline NLR and NER were associated with improved OS [HR: 0.504, 95% CI: 0.328-0.773, p = .002 and HR: 0.442, 95% CI: 0.288-0.681, p < .001, respectively] on univariate testing. After accounting for multiple covariates, our multivariate analysis found that lower pretreatment NER was associated with better ORR (by irRECIST) (OR: 2.199, 95% CI: 1.071-4.582, p = .033) and improved OS (HR: 0.480, 95% CI: 0.296-0.777, p = .003). Baseline NLR, 1-month NLR, and 1-month NER were not associated with ORR, PFS, or OS outcomes; but 1-month NER correlated with lower risk of grade ≥3 irAEs (OR: 0.392, 95% CI: 0.165-0.895, p = .029). Our findings suggest baseline NER merits additional investigation as a novel prognostic marker for advanced melanoma patients receiving anti-PD-1-based regimens.

Delphi Survey on the Current and Future Korean Guidelines for Isoniazid-Monoresistant Tuberculosis.

Purpose: Isoniazid-monoresistant tuberculosis (Hr-TB) has emerged as a global challenge, necessitating detailed guidelines for its diagnosis and treatment. We aim to consolidate the Korean guidelines for Hr-TB management by gathering expert opinions and reaching a consensus. Patients and Methods: A conventional Delphi method involving two rounds of surveys was conducted with 96 experts selected based on their clinical and research experience and involvement in nationwide tuberculosis studies and development of the Korean guidelines on tuberculosis. The survey consisted of three sections of questionnaires on diagnosis, treatment, and general opinions on Hr-TB. Results: Among the 96 experts, 72 (75%) participated in the two rounds of the survey. A majority of experts (96%) strongly agreed on the necessity of molecular drug susceptibility testing (DST) for isoniazid and rifampin resistance in all tuberculosis patients and emphasized the importance of interpreting mutation types (inhA or katG) and additional molecular DST for fluoroquinolones for confirmed isoniazid-resistant cases. Over 95.8% of experts recommended treating Hr-TB with a combination of rifampin, ethambutol, pyrazinamide, and levofloxacin for six months, without exceeding 12 months unless necessary. They also acknowledged the drawbacks of long-term pyrazinamide use due to its side effects and agreed on shortening its duration by extending the duration of the rest of the treatment with a modified combination of choice. Conclusion: This Delphi survey enabled Korean tuberculosis experts to reach a consensus on diagnosing and treating Hr-TB. These findings will be valuable for developing the upcoming revised Korean guidelines for Hr-TB management.

Cryobiopsy: A Breakthrough Strategy for Clinical Utilization of Lung Cancer Organoids.

One major challenge associated with lung cancer organoids (LCOs) is their predominant derivation from surgical specimens of patients with early-stage lung cancer. However, patients with advanced lung cancer, who are in need of chemotherapy, often cannot undergo surgery. Therefore, there is an urgent need to successfully generate LCOs from biopsy specimens. Conventional lung biopsy techniques, such as transthoracic needle biopsy and forceps biopsy, only yield small amounts of lung tissue, resulting in a low success rate for culturing LCOs from biopsy samples. Furthermore, potential complications, like bleeding and pneumothorax, make it difficult to obtain sufficient tissue. Another critical issue is the overgrowth of normal lung cells in later passages of LCO culture, and the optimal culture conditions for LCOs are yet to be determined. To address these limitations, we attempted to create LCOs from cryobiopsy specimens obtained from patients with lung cancer (n = 113). Overall, the initial success rate of establishing LCOs from cryobiopsy samples was 40.7% (n = 46). Transbronchial cryobiopsy enables the retrieval of significantly larger amounts of lung tissue than bronchoscopic forceps biopsy. Additionally, cryobiopsy can be employed for peripheral lesions, and it is aided via radial endobronchial ultrasonography. This study significantly improved the success rate of LCO culture and demonstrated that the LCOs retained characteristics that resembled the primary tumors. Single-cell RNA sequencing confirmed high cancer cell purity in early passages of LCOs derived from patients with advanced lung cancer. Furthermore, the three-dimensional structure and intracellular components of LCOs were characterized using three-dimensional holotomography. Finally, drug screening was performed using a specialized micropillar culture system with cryobiopsy-derived LCOs. LCOs derived from cryobiopsy specimens offer a promising solution to the critical limitations of conventional LCOs. Cryobiopsy can be applied to patients with lung cancer at all stages, including those with peripheral lesions, and can provide sufficient cells for LCO generation. Therefore, we anticipate that cryobiopsy will serve as a breakthrough strategy for the clinical application of LCOs in all stages of lung cancer.

Inside-out anal sacculectomy in small dog breeds and cats.

This report describes a new, simple and rapid surgical technique for the removal of anal sac in small dogs and cats. The anal sacs were simply everted using mosquito hemostatic forceps and excised with the aid of an electrocautery surgical unit. On the evaluation of postoperative complications, only one dog of 28 animals experienced short-term minor complications of mild fecal incontinence and scooting. Thus, we suggest that this new surgical technique is easy, inexpensive and time-saving and some of the complications with previously reported methods used for small dog breeds and cats may be avoided by using this technique.

Outcomes of patients with limited-stage plasmablastic lymphoma: A multi-institutional retrospective study.

Plasmablastic lymphoma (PBL) is a rare entity, commonly associated with immunosuppressed states such as human immunodeficiency virus (HIV) infection or solid organ transplant. The clinical course is characterized by high relapse rates and a poor prognosis, leading some clinicians to recommend aggressive frontline therapy. However, a specific review of limited stage (LS) PBL patients is not available to evaluate outcomes and justify treatment recommendations. We performed a retrospective review of LS PBL cases to provide insight into this rare disease. Our cohort consisted of 80 stage I or II PBL patients from 13 US academic centers. With a median follow up of 34 months (1-196), the 3-year progression-free survival (PFS) and overall survival (OS) of the entire cohort were 72% (95% CI 62, 83) and 79% (95% CI 70, 89), respectively. The 3-year PFS and OS of patients treated with frontline chemotherapy alone was 65% (95% CI 50, 84) and 71% (95% CI 56, 89), respectively, compared to 85% (95% CI 72, 100) and 96% (95% CI 89, 100), respectively, in patients treated with combined frontline chemotherapy with radiation consolidation. Our data demonstrate favorable outcomes in LS PBL with no improvements in outcome from aggressive frontline treatment including Hyper-CVAD or auto-SCT consolidation. Multivariate regression analysis (MRA) demonstrated improved PFS for patients receiving EPOCH based frontline therapy versus CHOP (HR: 0.23; p = 0.029). Frontline chemotherapy followed by radiation consolidation versus chemotherapy alone appeared to be associated with improved relapse and survival outcomes but did not show statistical significance in MRA.

Identification of phenocopies improves prediction of targeted therapy response over DNA mutations alone.

DNA mutations in specific genes can confer preferential benefit from drugs targeting those genes. However, other molecular perturbations can "phenocopy" pathogenic mutations, but would not be identified using standard clinical sequencing, leading to missed opportunities for other patients to benefit from targeted treatments. We hypothesized that RNA phenocopy signatures of key cancer driver gene mutations could improve our ability to predict response to targeted therapies, despite not being directly trained on drug response. To test this, we built gene expression signatures in tissue samples for specific mutations and found that phenocopy signatures broadly increased accuracy of drug response predictions in-vitro compared to DNA mutation alone, and identified additional cancer cell lines that respond well with a positive/negative predictive value on par or better than DNA mutations. We further validated our results across four clinical cohorts. Our results suggest that routine RNA sequencing of tumors to identify phenocopies in addition to standard targeted DNA sequencing would improve our ability to accurately select patients for targeted therapies in the clinic.

Interval design to identify the optimal biological dose for immunotherapy.

Immunotherapeutics have revolutionized the treatment of metastatic cancers and are expected to play an increasingly prominent role in the treatment of cancer patients. Recent advances in checkpoint inhibition show promising early results in a number of malignancies, and several treatments have been approved for use. However, the immunotherapeutic agents have been shown to have different mechanisms of antitumor activity from cytotoxic agents, and many limitations and challenges encountered in the traditional paradigm were recently pointed out for immunotherapy. I propose a desirability-based method to determine the optimal biological dose of immunotherapeutics by effectively using toxicity, immune response, and tumor response. Moreover, a new dose allocation algorithm of interval designs is proposed to incorporate immune response in addition to toxicity and tumor response. Simulation studies show that the proposed design has desirable operating characteristics compared to existing dose-finding designs. It also inherits the strengths of interval designs for dose-finding trials, yielding good performance with ease of implementation.

Challenges and opportunities in biomarker-driven trials: adaptive randomization.

In an era of precision medicine, as advanced technology such as molecular profiling at individual patient level has been developed and become increasingly accessible and affordable, biomarker-driven trials have been received a lot of attention and are expected to receive more attention in order to integrate clinical practice with clinical research. Biomarkers play a critical role to identify patients who are expected to get benefit from a treatment, and it is important to effectively incorporate the biomarkers into clinical trials to understand the biomarker-treatment relationship and increase the efficiency. We investigate incorporating biomarkers in adaptive randomization to identify patients who would respond better to the treatment and optimize the treatment allocation. The covariate-adjusted variants of the existing response-adaptive randomization are used to implement biomarker-driven randomization, and the performance of the biomarker-driven randomization is compared with the existing randomization methods, such as traditional fixed randomization with equal probability and response-adaptive randomization without incorporating biomarkers, under the group sequential design allowing early stopping due to superiority and futility. Various scenarios are taken into account to see the impact of the biomarker-driven randomization in the simulation study. It shows that the overall type I error rate is likely to be inflated by the effect of prognostic biomarkers. Several suggestions and considerations for the challenges are discussed to maintain the type I error rate at the nominal level.

Envelope-based partial partial least squares with application to cytokine-based biomarker analysis for COVID-19.

Partial least squares (PLS) regression is a popular alternative to ordinary least squares regression because of its superior prediction performance demonstrated in many cases. In various contemporary applications, the predictors include both continuous and categorical variables. A common practice in PLS regression is to treat the categorical variable as continuous. However, studies find that this practice may lead to biased estimates and invalid inferences (Schuberth et al., 2018). Based on a connection between the envelope model and PLS, we develop an envelope-based partial PLS estimator that considers the PLS regression on the conditional distributions of the response(s) and continuous predictors on the categorical predictors. Root-n consistency and asymptotic normality are established for this estimator. Numerical study shows that this approach can achieve more efficiency gains in estimation and produce better predictions. The method is applied for the identification of cytokine-based biomarkers for COVID-19 patients, which reveals the association between the cytokine-based biomarkers and patients' clinical information including disease status at admission and demographical characteristics. The efficient estimation leads to a clear scientific interpretation of the results.

Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer.

A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (BW=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity (AUC 0.77, Brown/Wilson p-value<0.0001). Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk.

Effect of abutment neck taper and cement types on the amount of remnant cement in cement-retained implant restorations: an in vitro study.

PURPOSE: The present study aims to analyze the effect of abutment neck taper and types of cement on the amount of undetected remnant cement of cement-retained implant prostheses. MATERIALS AND METHODS: Three neck taper angles (53°, 65°, 77°) and three types of cement (RMGI: resin-modified glass ionomer, ZPC: zinc phosphate cement, ZOE: zinc oxide eugenol cement) were used. For each group, the surface percentage was measured using digital image and graphic editing software. The weight of before and after removing remnant cement from the abutment-crown assembly was measured using an electronic scale. Two-way ANOVA and Duncan & Scheffe's test were used to compare the calculated surface percentage and weight of remnant cement (α = .05). RESULTS: There were significant differences in remnant cement surface percentage and weight according to neck taper angles (P < .05). However, there were no significant differences in remnant cement surface percentage and weight on types of cement. No interaction was found between neck taper angles and types of luting cement (P > .05). The wide abutment with a small neck taper angle showed the most significant amount of remnant cement. And the types of luting cement did not influence the amount of residual cement. CONCLUSION: To remove excess cement better, the emergence profile of the crown should be straight to the neck taper of the abutment in cement-retained implant restoration.