METHODS: MEDLINE, EMBASE and CENTRAL were systematically searched for randomized control trials (RCTs) from its inception until April 2020.
RESULTS: Six RCTs (n = 3139 patients) were included. In comparison to the GA alone, our meta-analysis demonstrated no significant difference in the cancer recurrence rate in patients who received the adjunctive use of RA in the routine care of GA (3 studies, n = 2380 patients; odds ratio 0.93, 95%CI 0.63-1.39, ρ = 0.73, certainty of evidence = very low). Our review also showed no significant difference in cancer-related mortality (2 studies, n = 545; odds ratio 1.20, 95%CI 0.83-1.74, ρ = 0.33, certainty of evidence = low), all-cause mortality (3 studies, n = 2653; odds ratio 0.98, 95%CI 0.69-1.39, ρ = 0.89, certainty of evidence = low) and duration of cancer-free survival (2 studies, n = 659; mean difference 0.00 years, 95%CI -0.25-0.25, ρ = 1.00, certainty of evidence = high).
CONCLUSION: This meta-analysis concluded that the adjunctive use of RA in the routine care of GA did not reduce cancer recurrence rate in cancer resection surgery. However, this finding needs to be interpreted with caution due to low level of evidence, substantial heterogeneity and potential risk of bias across the included studies.
STUDY REGISTRATION NUMBER: CRD42020171368.
MATERIAL AND METHODS: A systematic online search was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Eligible publications reporting the overall survival (OS) and/or disease-specific survival (DSS) were included. A total of 14 studies, including 17,869 patients, were considered for analysis. The impact of therapeutic modalities on survival was assessed, with a risk of bias assessment according to the Newcastle Ottawa Scale.
RESULTS: For RP, RT, and HT, the mean 10-year OS was 70.7% (95% CI 61.3-80.2), 65.8% (95% CI 48.1-83.3), and 22.6% (95% CI 4.9-40.3; p = 0.001), respectively. The corresponding 10-year DSS was 84.1% (95% CI 75.1-93.2), 89.4% (95% CI 70.1-108.6), and 50.4% (95% CI 31.2-69.6; p = 0.0127), respectively. Among all treatment combinations, RP displayed significant improvement in OS when included in the treatment (Z = 4.01; p < 0.001). Adjuvant RT significantly improved DSS (Z = 2.7; p = 0.007). Combination of RT and HT favored better OS in comparison to monotherapy with RT or HT (Z = 3.61; p < 0.001).
CONCLUSION: Improved outcomes in advanced PC were detected for RP plus adjuvant RT vs. RP alone and RT plus adjuvant HT vs. RT alone with comparable survival results between both regimens. RP with adjuvant RT may present the modality of choice when HT is contraindicated.
METHODS: Altogether 67 esophageal squamous cell carcinomas histologically diagnosed between 1 January 2004 and 31 December 2014 at the Department of Pathology, University of Malaya Medical Center, Malaysia were considered for HPV analysis using two commercially available methods, polymerase chain reaction with flow-through hybridization (21 HPV GenoArray Diagnostic Kit) and multiplex real-time polymerase chain reaction (Anyplex II HPV28 Detection). The DNA amplifiability of the formalin-fixed, paraffin-embedded tumor was checked by amplification of a 268 bp segment of the human β-globin gene (GH20/PC04) prior to HPV detection.
RESULTS: HPV detection was finally carried out in 51 patients. HPV16 was detected in the moderately differentiated, stage IV lower esophageal tumor of a 32-year-old Malaysian-born Chinese woman by both methods. Except for a predilection for Indians, the clinical characteristics of esophageal squamous cell carcinomas in this Malaysian cohort were generally similar to those of other populations.
CONCLUSION: It appears that HPV is rare and an unlikely oncovirus in esophageal squamous cell carcinomas of Malaysians.
Materials and Methods: We analyzed 101 cases of prostate adenocarcinoma diagnosed from January 2011 to June 2015 in 100 patients. Immunohistochemical staining of ER-beta and Ki67 was analyzed according to Gleason score categorized into prognostic groups of 1 to 5. Double-immunofluorescent staining of ER-beta and Ki67 was performed in a total of 20 cases to study the co-expression and the relationship between these markers within the same tumor.
Results: A total of 53 of 101 cases (52.5%) were positive for ER-beta expression. There was a positive correlation whereby a high percentage of ER-beta expression was seen in the higher prognostic groups (groups 4 and 5; p=0.007). High Ki67 expression was observed in the higher prognostic group, whereas low Ki67 or negative expression was found in the lower prognostic group (p<0.001). The majority of cases evaluated with double-immunofluorescent staining (14/20) showed co-expression of ER-beta and Ki67 at the individual cell level.
Conclusions: ER-beta and Ki67 are independent tumor markers in high prognostic groups. Hence, co-expression of ER-beta and Ki67 indicates a more aggressive tumor with a poorer prognosis.
METHODS: Using Singapore Malaysia Hospital-Based Breast Cancer Registry, clinical information was retrieved from 7064 stage I to III breast cancer patients who were diagnosed between 1990 and 2011 and underwent surgery. Predicted and observed probabilities of positive nodes and survival were compared for each subgroup. Calibration was assessed by plotting observed value against predicted value for each decile of the predicted value. Discrimination was evaluated by area under a receiver operating characteristic curve (AUC) with 95 % confidence interval (CI).
RESULTS: The median predicted probability of positive lymph nodes is 40.6 % which was lower than the observed 43.6 % (95 % CI, 42.5 %-44.8 %). The calibration plot showed underestimation for most of the groups. The AUC was 0.71 (95 % CI, 0.70-0.72). Cancermath predicted and observed overall survival probabilities were 87.3 % vs 83.4 % at 5 years after diagnosis and 75.3 % vs 70.4 % at 10 years after diagnosis. The difference was smaller for patients from Singapore, patients diagnosed more recently and patients with favorable tumor characteristics. Calibration plot also illustrated overprediction of survival for patients with poor prognosis. The AUC for 5-year and 10-year overall survival was 0.77 (95 % CI: 0.75-0.79) and 0.74 (95 % CI: 0.71-0.76).
CONCLUSIONS: The discrimination and calibration of CancerMath were modest. The results suggest that clinical application of CancerMath should be limited to patients with better prognostic profile.
MATERIALS AND METHODS: Paraffin blocks of 133 CRCs were retrieved from the Department of Pathology, King Abdulaziz University, Jeddah, Saudi Arabia. Immunostaining was done using antibody to clusterin. Staining expression in 10% of malignant cells was used as a cut-off to determine low immunostaining and high immunostaining. Statistical tests were used to evaluate the association of clusterin immunostaining with clinicopathological parameters.
RESULTS: Immunohistochemical results showed clusterin low immunostaining in CRC and nodal metastases. No association was found between clusterin immunostaining and tumour grade, age, tumour invasiveness, distant metastases, vascular invasion, nodal metastases, relapse, and survival.
CONCLUSION: Our study showed low clusterin immunostaining in CRC with lack of association with prognostic indicators in CRC. These results raise the controversy of understanding the role of clusterin in CRC. Further molecular studies are required to explore more about possible mechanisms of clusterin association with tumorigenicity, apoptosis, tumour growth progression, local and vascular invasion, and metastasis of CRC.
METHODS: Data were retrieved for major SGC patients diagnosed between 1988 and 2011 from Surveillance, Epidemiology, and End Results program.
RESULTS: We have included 5446 patients with major SGC. Most patients had parotid gland cancer (84.61%). Patients having >18 ELNs, >4 PLNs, and >33.33% LNR were associated with a worse survival. Moreover, older age, male patients, grade IV, distant stage, unmarried patients, submandibular gland cancer, and received chemotherapy but not received surgery were significantly associated with a worse survival.
CONCLUSIONS: We demonstrated that patients with >18 ELNs and >4 PLNs counts, and >33.33% LNR were high-risk group patients. We strongly suggest adding the ELNs and PLNs counts and/or LNR into the current staging system.
METHODS: A large hospital-based breast cancer dataset retrieved from the University Malaya Medical Centre, Kuala Lumpur, Malaysia (n = 8066) with diagnosis information between 1993 and 2016 was used in this study. The dataset contained 23 predictor variables and one dependent variable, which referred to the survival status of the patients (alive or dead). In determining the significant prognostic factors of breast cancer survival rate, prediction models were built using decision tree, random forest, neural networks, extreme boost, logistic regression, and support vector machine. Next, the dataset was clustered based on the receptor status of breast cancer patients identified via immunohistochemistry to perform advanced modelling using random forest. Subsequently, the important variables were ranked via variable selection methods in random forest. Finally, decision trees were built and validation was performed using survival analysis.
RESULTS: In terms of both model accuracy and calibration measure, all algorithms produced close outcomes, with the lowest obtained from decision tree (accuracy = 79.8%) and the highest from random forest (accuracy = 82.7%). The important variables identified in this study were cancer stage classification, tumour size, number of total axillary lymph nodes removed, number of positive lymph nodes, types of primary treatment, and methods of diagnosis.
CONCLUSION: Interestingly the various machine learning algorithms used in this study yielded close accuracy hence these methods could be used as alternative predictive tools in the breast cancer survival studies, particularly in the Asian region. The important prognostic factors influencing survival rate of breast cancer identified in this study, which were validated by survival curves, are useful and could be translated into decision support tools in the medical domain.
METHODS: In this prospective real-world study, we recruited and followed up patients diagnosed with CAT treated with rivaroxaban or standard of care as a control for 12 months or until death. Baseline characteristics were collected at the study entry. The primary outcomes were recurrent DVT or PE and death within 12 months after treatment initiation. Safety outcomes were composite outcomes of major and minor bleeding. Results: A total of 80 patients confirm CAT with radiological imaging were recruited; 39 patients were evaluated in the control arm and 41 patients in the rivaroxaban arm. The 12 months cumulative CAT recurrence rate was 46.2% in control and 39% in rivaroxaban (p=0.519). The 12-month death was not a statistically significant difference between both arms (20.5% vs. 31.7%, p=0.255). The cumulative rate of composite safety outcomes was similar in both groups (17.9% vs. 12.2%, p=0.471).
CONCLUSION: The result of this small but important real-world evidence proofs that rivaroxaban is an effective and safe alternative to the standard of care for CAT in Malaysia's cancer population.
METHOD: The protocol of this review is registered on PROSPERO(CRD42020190882). A comprehensive literature search was performed on Medline, Embase and Cochrane CENTRAL using MeSH terms and keywords for randomised controlled trials and observational studies on the topic. Risks of biases were assessed using the Cochrane RoB tool and the Newcastle-Ottawa Scale. For localised RCC, immediate surgery [including partial nephrectomy (PN) and radical nephrectomy (RN)] and delayed surgery [including active surveillance (AS) and delayed intervention (DI)] were compared. For metastatic RCC, upfront versus deferred cytoreductive nephrectomy (CN) were compared.
RESULTS: Eleven studies were included for quantitative analysis. Delayed surgery was significantly associated with worse cancer-specific survival (HR 1.67, 95% CI 1.23-2.27, p
Objective: To determine the additional relationship between factors discovered by searching for sociodemographic and metastasis factors, as well as treatment outcomes, which could help improve the prediction of the survival rate in cancer patients. Material and Methods. A total of 56 patients were recruited from the ambulatory clinic at the Hospital Universiti Sains Malaysia (USM). In this retrospective study, advanced computational statistical modeling techniques were used to evaluate data descriptions of several variables such as treatment, age, and distant metastasis. The R-Studio software and syntax were used to implement and test the hazard ratio. The statistics for each sample were calculated using a combination model that included methods such as bootstrap and multiple linear regression (MLR).
Results: The statistical strategy showed R demonstrates that regression modeling outperforms an R-squared. It demonstrated that when data is partitioned into a training and testing dataset, the hybrid model technique performs better at predicting the outcome. The variable validation was determined using the well-established bootstrap-integrated MLR technique. In this case, three variables are considered: age, treatment, and distant metastases. It is important to note that three things affect the hazard ratio: age (β 1: -0.006423; p < 2e - 16), treatment (β 2: -0.355389; p < 2e - 16), and distant metastasis (β 3: -0.355389; p < 2e - 16). There is a 0.003469102 MSE for the linear model in this scenario.
Conclusion: In this study, a hybrid approach combining bootstrapping and multiple linear regression will be developed and extensively tested. The R syntax for this methodology was designed to ensure that the researcher completely understood the illustration. In this case, a hybrid model demonstrates how this critical conclusion enables us to better understand the utility and relative contribution of the hybrid method to the outcome. The statistical technique used in this study, R, demonstrates that regression modeling outperforms R-squared values of 0.9014 and 0.00882 for the predicted mean squared error, respectively. The conclusion of the study establishes the superiority of the hybrid model technique used in the study.