Abstrak. Tujuan penelitian ini adalah untuk mengindentifikasi dan menganalisis serta memberikan gambaran tentang karakteristik sifat kualitatif ayam bangkok di Kota Kendari. Penelitian ini dilaksanakan pada bulan November 2021 sampai dengan Desember 2021 betempat di Kota Kendari Sulawesi Tenggara. Bahan yang digunakan dalam penelitian ini adalah 300 ekor ayam bangkok, terdiri dari 150 ekor ayam bangkok jantan dan 150 ekor ayam bangkok betina. Umur ayam bangkok yang digunakan dalam penelitian ini adalah dengan kisaran umur 6 bulan sampai 2 tahun. Variabel yang diamati pada penelitian ini adalah sifat kualitatif yang meliputi warna bulu, bentuk jengger, dan warna shank. Hasil penelitian menunjukkan bahwa frekuensi gen pengontrol tertinggi karakterisik eksternal pada ayam bangkok di Kota Kendari adalah warna bulu berwarna (ii) (100%), pola bulu liar (e+_) (37,00%), kerlip bulu emas (ss) (66,66%) corak bulu polos (bb) (73,66%), warna shank putih (idid) (50%) dan bentuk jengger pea (P_) (94,33%).Kata Kunci : Ayam Bangkok, Sifat Kualitatif, Kota Kendari
This retrospective study aimed to evaluate the distribution pattern and prognostic value of 21-gene recurrence score (RS) in Chinese patients with mucinous breast cancer (MC) and compared with infiltrating ductal carcinoma (IDC).Patients diagnosed with MC or IDC from January 2010 to January 2017 were retrospectively recruited. Reverse transcriptase-polymerase chain reaction assay of 21 genes was conducted to calculate the RS. Univariate and multivariate analyses were performed to assess the association between RS and clinicopathological factors. Survival outcomes including disease-free survival (DFS) and overall survival (OS) were estimated by Kaplan-Meier method and compared by log-rank test.The MC cohort included 128 patients and the IDC cohort included 707 patients. The proportions of patients with a low (RS < 18), intermediate (18-30), or high risk (RS > 30) were 32.0%, 48.4%, and 19.5% in MC cohort, and 26.9%, 46.8% and 26.3% in IDC cohort. The distribution of RS varied significantly according to different Ki-67 index and molecular subtype in both cohorts. Moreover, the receipt of chemotherapy was associated with RS in both cohorts. Among patients with MC, tumor stage was related to the DFS (p=0.040). No significant differences in DFS and OS were found among MC patients in different RS risk groups (OS, p=0.695; DFS, p=0.926).RS was significantly related to Ki-67 index and molecular subtypes in MC patients, which is similar in IDC patients. However, RS was not able to predict DFS and OS in patients with MC.
Abstract
This research aims to determine the effect of leverage, sales growth, and intellectual capital on financial distress. The independent variables used are leverage (DER), sales growth (SG), and intellectual capital (IC). The population in this study were various industrial sector companies for the 2015-2019 period. The sampling technique used purposive sampling technique with 80 sample data. The data analysis technique used is multiple linear regression analysis on SPPS version 25. Partially leverage (DER) has a significant negative effect on financial distress. Sales growth (SG) has a significant positive effect on financial distress. Meanwhile, intellectual capital (IC) has no influence on financial distress.
Keyword: leverage, sales growth, intellectual capital, and financial distress
Abstrak
Penelitian ini bertujuan untuk mengetahui pengaruh leverage, sales growth, dan intellectual capital terhadap financial distress. Variabel independen yang digunakan leverage (DER), sales growth (SG), dan intellectual capital (IC). Populasi dalam penelitian ini adalah perusahaan sektor aneka industri untuk periode 2015-2019. Teknik pengambilan sampel menggunakan teknik purposive sampling dengan 80 data sampel. Teknik analisis data yang digunakan adalah analisis regresi linier berganda pada SPPS versi 25. Secara parsial leverage (DER) memiliki pengaruh negatif signifikan terhadap financial distress. Sales growth (SG) memiliki pengaruh positif signifikan terhadap financial distress. Sedangkan intellectual capital (IC) tidak memiliki pengaruh terhadap financial distress.
Kata Kunci: leverage, sales growth, intellectual capital dan financial distress
Despite the rapid growing of cancer survivors, prior cancer history is a commonly adopted exclusion criterion. Whether prior cancer will impact the survival of patients with advanced breast cancer (ABC) remains uncertain.Patients with ABC diagnosed between 2004 and 2010 were identified using Surveillance, Epidemiology, and End Results (SEER) database. Timing, stage, and type were used to characterize prior cancer. Multivariable analyses using propensity score-adjusted Cox regression and competing risk regression were conducted to evaluate the prognostic effect of prior cancer on overall survival (OS) and breast cancer-specific survival (BCSS).A total of 14,176 ABC patients were identified, of whom 10.5% carried a prior cancer history. The most common type of prior cancer was female genital cancer (32.4%); more than half (51.7%) were diagnosed at localized stage; most were diagnosed more than 5 years (42.9%) or less than 1 year (28.3%) prior to the index cancer. In multivariate analyses, patients with prior cancer presented a slightly worse OS (hazard ratio, 1.18; 95% confidence interval [CI], 1.07 to 1.30; p=0.001) but a better BCSS (subdistribution hazard ratio, 0.64; 95% CI, 0.56 to 0.74; p < 0.001). In subset analyses, no survival detriment was observed in patients with prior malignancy from head and neck or endocrine system, at in situ or localized stage, or diagnosed more than 4 years.Prior cancer provides an inferior OS but a superior BCSS for patients with ABC. It does not affect the survival adversely in some subgroups and these patients should not be excluded from clinical trials.
Abstract Background: Targeted therapies have largely improved prognosis of human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Yet, disease can still progress rapidly for some patients in the first two years after diagnosis. Our study aimed to establish a nomogram model to predict 2-year breast cancer-specific survival (BCSS) in early HER2-positive breast cancer patients. Methods: A total of 32,481 HER2-positive patients derived from Surveillance, Epidemiology, and End Results (SEER) database were included in the construction of nomogram. Concordance index (C-index) and calibration curve were used to evaluate the discrimination ability and predictive accuracy. We also tested the model in 804 patients from Shanghai Jiao Tong University Breast Cancer Data Base (SJTU-BCDB). Results: Age, estrogen receptor (ER) status, progesterone receptor (PR) status, histologic type, T stage and N stage were selected to construct the nomogram according to multivariable analysis. The 2-year BCSS rate was 95% and 60% for patients at low risk (<8 points) and high risk (>13 scores) respectively. The C-index of model derived from SEER database is 0.81 (95%CI 0.79-0.83). Sensitivity analysis was performed in patients undergoing breast surgeries with the C-index of 0.81 (95%CI 0.79-0.83). Validation in 804 patients from SJTU-BCDB showed respective C-index of 0.77 (95%CI, 0.62-0.92) in total population, 0.67 (95%CI 0.44-0.90) in patients receiving anti-HER2 therapy and 0.90 (95%CI 0.81-0.90) in those without targeted therapy. Conclusions: The novel nomogram can predict 2-year survival outcome in HER2-positive patients independent of receiving anti-HER2 therapy or not and help clinicians to adjust therapeutic strategies for those patients with higher risk.
Purpose: The objective of this study was to evaluate the American Joint Committee on Cancer (AJCC) pathological prognostic stage among patients with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) and to propose a modified score system if necessary. Methods: Women diagnosed with IDC and ILC during 2010-2015 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively identified. Disease-specific survival (DSS) and overall survival (OS) were estimated by Kaplan-Meier method. Predictive performances of different staging systems were evaluated based on Harrell concordance index (C-index) and Akaike Information Criterion (AIC). Multivariate Cox models were conducted to build preferable score systems. Results: A total of 184,541 female patients were included in the final analyses, with a median follow-up of 30.0 months. In IDC cohort, the pathological prognostic stage (C-index, 0.8281; AIC, 110274.5) was superior to the anatomic stage (C-index, 0.8125; AIC, 112537.0; P < 0.001 for C-index) in risk stratification with respect to DSS. In ILC cohort, the prognostic stage (C-index, 0.8281; AIC, 7124.423) didn't outperform the anatomic stage (C-index, 0.8324; AIC, 7144.818; P = 0.748 for C-index) with respect to DSS. Similar results were observed with respect to OS. The score system defined by anatomic stage plus grade plus estrogen receptor and progesterone receptor (AS+GEP) allows for better staging (C-index, 0.8085; AIC, 7178.448) for ILC patients. Conclusion: Compared with anatomic stage, the pathological prognostic stage provided more accurate stratification for patients with IDC, but not for patients with ILC. The AS+GEP score system may fit ILC tumors better.
Abstract Background: Despite low invasiveness in tumor biology and high sensitivity to endocrine therapy (ET), about 5% to 10% patients with ER+ breast cancer will relapse early in the first two years (yrs) after initiation of ET. Resistance to ET remains one of the leading causes of treatment failure. Methods: Patients with ER+/HER2- breast cancer were retrospectively identified from Shanghai Ruijin Hospital. Expression of 16 cancer-related genes were measured using RT-PCR based on 21-gene assay. Cox proportional hazard model was developed to identify the clinical and genomic variables associated with pre-2-yr relapse with P value of less than .10. Both the landmark analyses and tests for the interaction between genes expression and time were performed to identify the inconsistent effects of individual genes on relapse in two time periods. Finally, a risk score was established based on the clinical and genomic variables with the shrinkage correction and validated using a bootstrap method. Relationship between the risk score and log-hazard ratio of early relapse was presented by the cubic smoothing spline method. The primary endpoint was invasive disease-free survival (IDFS) and secondary endpoints were distant relapse-free survival (DRFS) and overall survival (OS). Results: A total of 1,227 patients were identified. In univariate Cox regression, both the age over 50 yrs (HR 0.55, 95% CI 0.27 - 1.10) and tumor size greater than 2cm (HR 3.26, 95% CI 1.61 - 6.60) were independent prognostic factors for early relapse. As for genomic variables, higher expression of ER (HR 0.79, 95% CI 0.64 - 0.97), PGR (HR 0.83, 95% CI 0.71 - 0.96), BCL2 (HR 0.75, 95% CI 0.55 - 1.03), CD68 (HR 0.66, 95% CI 0.47 - 0.91), GSTM1 (HR 0.78, 95% CI 0.58 - 1.04), and BAG1 (HR 0.69, 95% CI 0.49 - 0.97) were associated with increased early relapse. Of the genomic variables, the HR of PGR, CD68, and BAG1 were in the opposite direction for 2 time periods (interaction P .026, .003, and .011, respectively; Table 1). A scoring system was established based on 2 clinical variables and 6 genomic variables with the shrinkage adjustment (C-index, 0.68; bootstrap validated C-index, 0.69; Table 2). The risk score tended to be associated with early relapse linearly using cubic spline method. When used as a categorical variable with the cutoff point decided by X-tile, risk score higher than 2.5 was also associated with increased early relapse (HR 3.23, 95% CI 1.56 - 6.69, P< .001). Likewise, the score remained an independent predictor for 2-yr DRFS (HR 6.18, 95% CI 1.79 - 21.34, P = .001) and OS (HR 4.57, 95% CI 1.02 - 20.43, P = .029). Conclusion: The scoring system reported herein, taking into account both the clinical and genomic variables, may inform prognosis and endocrine responsiveness. For patients with high risk of early relapse, treatment escalation may be considered. Table 1. Univariate analysis for individual genes by time periods.0-5 yrs0-2 yrs2-5 yrsInteraction PHR (95% CI)PHR (95% CI)PHR (95% CI)PEstrogen moduleER0.92 (0.79-1.07).2730.79 (0.64-0.97).0241.05 (0.86-1.28).651.053PGR0.93 (0.84-1.04).2030.83 (0.71-0.96).0131.05 (0.91-1.21).545.026BCL20.84 (0.68-1.04).1050.75 (0.55-1.03).0740.91 (0.68-1.22).540.374SCUBE20.92 (0.81-1.04).1990.93 (0.77-1.12).4570.91 (0.77-1.08).290.878Proliferation moduleKi671.25 (1.01-1.55).0391.31 (0.94-1.83).1081.21 (0.92-1.60).178.710STK151.12 (0.94-1.33).2221.03 (0.77-1.37).8421.18 (0.94-1.47).152.467Survivin1.09 (0.91-1.30).3691.07 (0.80-1.43).6551.10 (0.87-1.38).428.888CCNB11.07 (0.87-1.32).5260.88 (0.64-1.21).4231.23 (0.94-1.61).126.110MYBL21.16 (0.97-1.40).1071.13 (0.84-1.52).4321.19 (0.94-1.50).151.783Invasion moduleMMP111.11 (0.95-1.29).2051.03 (0.82-1.31).7901.16 (0.95-1.43).154.460CTSL21.07 (0.89-1.29).4491.16 (0.87-1.54).3221.02 (0.80-1.30).863.516HER2 moduleGRB71.11 (0.88-1.41).3700.89 (0.62-1.26).5041.30 (0.96-1.75).085.105HER20.91 (0.75-1.11).3510.89 (0.66-1.21).4620.92 (0.71-1.20).550.865GSTM10.81 (0.67-0.99).0360.78 (0.58-1.04).0880.84 (0.65-1.09).192.673CD680.96 (0.76-1.21).7040.66 (0.47-0.91).0111.28 (0.95-1.73).106.003BAG10.97 (0.76-1.22).7690.69 (0.49-0.97).0311.24 (0.92-1.68).158.011 Table 2. Univariate β coefficients and shrinkage factor for clinical and genomic variables.BetaSEHR95% CIPShrinkage factorClinical variables0.857Age, vs ≤ 50 yrs-0.6000.3560.550.27-1.10.093Tumor size, vs ≤ 2cm1.1810.3603.261.61-6.60.001Genomic variables0.313ER-0.2410.1070.790.64-0.97.024PGR-0.1900.0760.830.71-0.96.013BCL2-0.2860.1600.750.55-1.03.074CD68-0.4210.1650.660.47-0.91.011GSTM1-0.2540.1490.780.58-1.04.088BAG1-0.3780.1750.690.49-0.97.031Abbreviation: SE, standard error; HR, hazard ratio; CI, confidence interval. Citation Format: Caijin Lin, Jiayi Wu, Shuning Ding, Lisa Andriani, Weilin Chen, Deyue Liu, Li Zhu. A novel scoring system based on the clinical and genomic variables to predict the early relapse in estrogen receptor-positive/HER2-negative (ER+/HER2-) breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-11-15.
Penelitian ini bertujuan untuk mengetahui pengaruh struktur modal dan manajemen laba terhadap PPh Badan Terhutang pada Perusahaan Sub Sektor Plastik dan Kemasan yang terdaftar di Bursa Efek Indonesia Periode 2018-2020. Data penelitian diperoleh dari Bursa Efek Indonesia (www.idx.co.id dan www.sahamok.com) tentang struktur modal dan manajemen laba terhadap PPh Badan Terhutang pada Perusahaan Sub Sektor Plastik dan Kemasan yang terdaftar di Bursa Efek Indonesia sebanyak 8 perusahaan yang telah memenuhi kriteria. Data diolah dengan menggunakan SPSS V25, yaitu regresi linear berganda, hipotesis, uji t, uji F dan koefisien determinasi (R2). Hasil penelitian ini menunjukkan bahwa diperoleh persamaan linear berganda yaitu Y = 8.892.860.226 + 9,596.007 - 0,001. Berdasarkan persamaan ini Struktur Modal dan Manajemen Laba terhadap PPh Badan Terhutang, secara parsial masing-masing variabel Struktur Modal dan Manajemen Laba tidak berpengaruh dan tidak signifikan terhadap PPh BadanTerhutang pada Perusahaan Sub Sektor Plastik dan Kemasan yang terdaftar di Bursa Efek Indonesia. Secara simultan Struktur Modal dan Manajemen Laba tidak berpengaruh positif dan tidak signifikan terhadap PPh Badan Terhutang pada Perusahaan Sub Sektor Plastik dan Kemasan yang terdaftar di Bursa Efek Indonesia. Nilai R square sebesar 0,340% atau 3,4% yang berarti 3,4% PPh Badan Terhutang diperngaruhi oleh variabel Struktur Modal dan Manajemen Laba sedangkan sisanya sebesar 96,6% dipengaruhi oleh variabel lain yang tidak diteliti dalam penelitian ini
Metastatic breast cancer (MBC) is a highly heterogeneous disease and bone is one of the most common metastatic sites. This retrospective study was conducted to investigate the clinical features, prognostic factors and benefits of surgery of breast cancer patients with initial bone metastases.From 2010 to 2015, 6,860 breast cancer patients diagnosed with initial bone metastasis were analyzed from Surveillance, Epidemiology, and End Results (SEER) database. Univariate and Multivariable analysis were used to identify prognostic factors. A nomogram was performed based on the factors selected from cox regression result. Survival curves were plotted according to different subtypes, metastatic burdens and risk groups differentiated by nomogram.Hormone receptor (HR) positive/human epidermal growth factor receptor 2 (HER2) positive patients showed the best outcome compared to other subtypes. Patients of younger age (<60 years old), white race, lower grade, lower T stage (<=T2), not combining visceral metastasis tended to have better outcome. About 37% (2,249) patients received surgery of primary tumor. Patients of all subtypes could benefit from surgery. Patients of bone-only metastases (BOM), bone and liver metastases, bone and lung metastases also showed superior survival time if surgery was performed. However, patients of bone and brain metastasis could not benefit from surgery (p = 0.05). The C-index of nomogram was 0.66. Cutoff values of nomogram point were identified as 87 and 157 points, which divided all patients into low-, intermediate- and high-risk groups. Patients of all groups showed better overall survival when receiving surgery.Our study has provided population-based prognostic analysis in patients with initial bone metastatic breast cancer and constructed a predicting nomogram with good accuracy. The finding of potential benefit of surgery to overall survival will cast some lights on the treatment tactics of this group of patients.
Abstract Background: The objective of the current study was to validate the prognostic staging system (PS) proposed in AJCC 8th edition staging manual among patients with invasive ductal carcinoma (IDC) and patients with invasive lobular carcinoma (ILC) respectively, and to compare the predictive performances of PS in both cohorts. Method: Patients diagnosed with IDC and ILC from 2010 to 2015 in the Surveillance, Epidemiology and End Results (SEER) database were retrospectively identified. Patients were restaged according to anatomic staging system (AS) and PS. Disease-specific survival (DSS) and overall survival (OS) were estimated by Kaplan-Meier method. The predictive performances of different staging systems were quantified and compared based on Harrell’s concordance index (C-index) and Akaike information criterion (AIC) calculated from Cox models. New staging score systems were established by assigning points to DSS-associated prognostic factors to improve risk stratification. Results: A total of 184,541 female patients were included in the final analyses, with 166,084 (90%) cases in the IDC cohort while 18,475 (10%) cases in the ILC cohort. Stage distribution and survival outcomes of different stages were showed in Table1. In IDC cohort, the PS (C-index, 0.8281; AIC, 110274.5) showed superiority in risk stratification compared with the AS (C-index, 0.8125; AIC, 112537.0; P<0.001 for C-index) with respect to DSS. In ILC cohort, the PS (C-index, 0.8281; AIC, 7124.423) was not superior to the AS (C-index, 0.8324; AIC, 7144.818; P=0.748 for C-index) in prognosis prediction with respect to DSS. Similar results were observed with respect to OS. Among three score systems specially designed for ILC patients, the score system defined by AS plus grade plus estrogen receptor and progesterone receptor (AS+GEP) allowed for better staging (C-index, 0.8085; AIC 7178.448). Detailed point assignments were listed in Table2. Conclusion: Compared with AS, the PS provided more accurate stratification for patients with IDC, but not for patients with ILC. The AS+GEP score system may fit ILC tumors better. Further investigation was needed to refine tumor staging. Table1. Distribution and survival outcomes by anatomic stages and prognostic stages in IDC cohort(N=166,084) and ILC cohort(N=18,475).StageIDC cohortILC cohortN (%)4-year DSS4-year OSN (%)4-year DSS5-year OSASIA85807(51.7)98.7195.687779(42.1)99.2395.99IB4500(2.7)97.7495.63326(1.8)98.6394.57IIA38186(23.0)95.2591.314596(24.9)97.4392.75IIB19762(11.9)91.2387.282628(14.2)96.3492.13IIIA10879(6.6)84.5381.462010(10.9)92.0587.14IIIB2831(1.7)75.3368.83202(1.1)74.6568.15IIIC4119(2.5)71.8267.22916(5.0)77.5573.94PSIA102448(61.7)98.8695.7012156(65.9)98.8095.27IB25722(15.5)95.7292.203553(19.3)95.4991.22IIA17329(10.4)91.0087.13757(4.1)95.1189.06IIB6599(4.0)86.7183.40541(2.9)91.6886.15IIIA7092(4.3)82.3078.281049(5.7)83.0177.15IIIB3431(2.1)76.0071.12313(1.7)72.3369.12IIIC3463(2.1)57.4352.3887(0.5)52.5348.09 Table 2. Univariate and multivariate analyses for factors associated with DSS and point assignment in ILC cohort.FactorUnivariate analysisMultivariate analysisModel AS+GModel AS+GEPHRPHRPHRPPointStageIA1/11/0IB1.84<0.0011.750.3541.870.2690IIA3.34<0.0013.15<0.0013.15<0.0011IIB5.31<0.0014.91<0.0015.04<0.0012IIIA10.74<0.0019.76<0.0019.82<0.0013IIIB30.16<0.00126.49<0.00123.86<0.0014IIIC31.41<0.00127.90<0.00126.06<0.0014Grade11/11/021.75<0.0011.43<0.0012.380.014134.30<0.0012.47<0.0012.06<0.0011ER statusPositive1/1/0Negative6.85<0.0012.51<0.0011PR statusPositive1/1/0Negative2.47<0.0011.75<0.0011HER2 statusNegative1/Positive1.270.253Abbreviations for tables: AS, anatomic staging system; PS, prognostic staging system; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; DSS, disease -specific survival; OS, overall survival; HR, hazard ratio; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2; AS+G,anatomic stage plus grade; AS+GEP, anatomic stage plus grade plus estrogen receptor plus progesterone receptor. Citation Format: Shuning Ding, Jiayi Wu, Caijin Lin, Lisa Andriani, Weilin Chen, Deyue Liu, Li Zhu. Comparison of the AJCC eighth edition prognostic stage and anatomic stage in different histological breast cancer types and proposal of a novel score system [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-06-23.
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