Outcome of FOLFOX and Modified DCF Chemotherapy Regimen in Patients with Advanced Gastric Adenocarcinoma

Objectives: Chemotherapy is used as an indispensable therapy for advanced gastric cancer. Different chemotherapy regimens have been used for this purpose. Toxicity due to the Chemotherapy drugs is one limiting factor. In this study we aim to compare the efficacy and toxicity of two regimens FOLFOX (leucoverin, 5-fluorouracil and oxaliplatin) and modified DCF (mDCF) (docetaxel, cisplatin, and 5-fluorouracil) in patients with advanced gastric adenocarcinoma. Methods: In this analytical cross-sectional study, 47 patients treated with FOLFOX regimen and 57 patients treated with mDCF regimen were recruited, Patients in both groups were compared for demographic findings, response rate, mortality rate, overall survival (OS) and progression free survival (PFS). Results: In FOLFOX and mDCF group, complete response (CR) occurred in 4.3% and 5.3%, partial response (PR) in 42.6% and 29.8%, stable disease in 34% and 52.6% and disease progression in 19.1% and 12.3%, respectively (p=0.25). Overall response rate was 48.9% and 56.1%, respectively. There was no significant difference between two regimens in OS and PFS (p=0.22). mDCF compared to FOLFOX had significantly higher hematologic, gastrointestinal complications, as well as creatinine rise, stomatitis and hair loss, but peripheral neuropathy was significantly lower. Conclusion: The results of current study showed that in patients with advanced gastric adenocarcinoma, FOLFOX regimen compared to mDCF regimen have similar ORR, OS and PFS. Toxicity rate are also lower in FOLFOX group, thus it seems a better regimen for chemotherapy.     

Medicaid Reimbursement for Screening and Brief Intervention: Amending the Medicaid State Plan and Approving State Appropriations for the Medicaid State Match

The federal government is strongly committed to the early identification (screening) of individuals with substance use disorders (SUDs) and the provision of clinically appropriate brief interventions for nondependent users of alcohol and drugs (i.e., persons with alcohol or drug abuse disorders) as well as referral to specialty addictions treatment for those with dependence (alcohol or drug addiction). However, limited third-party reimbursement of healthcare providers (particularly primary care and emergency department professionals) poses significant implementation barriers and sustainability challenges for projects, including State grantees that have been awarded Screening, Brief Intervention and Referral to Treatment (SBIRT) Program funding through the Substance Abuse and Mental Health Services Administration (SAMHSA) Center for Substance Abuse Treatment (CSAT). Although the Centers for Medicare and Medicaid (CMS) authorized Medicaid program reimbursement for screening and brief intervention (SBI) services to begin in 2007, few providers realize that before state Medicaid offices can begin reimbursement for these services, states must submit State Plan Amendment requests to CMS for approval. Further, before states can submit State Plan Amendment requests, they must first obtain legislative approval for state appropriations to support the state's portion of the expense of delivering the new services (the State's “Medicaid match”). States can leverage these requests by demonstrating that SBI services are effective and cost-effective, and that they lead to measurable cost offsets. This column is adapted from a SAMHSA-funded Medicaid reimbursement manual developed to help SBIRT grantees make cogent arguments for these state-level changes (Fornili & Alemi, 2007).     

Participation in Teleconference Support Groups: Application to Drug-Using Pregnant Patients

This paper describes our experience using telephone conference calls to conduct support groups for chemically-dependent women. Forty-seven women agreed to participate in regular, weekly support groups that were conducted by two chemical dependency counselors. Counselors attempted to conduct 59 support groups via a telephone conferencing system. Our data indicated that attendance at these sessions was poor. Seventeen sessions had no participants. No group sessions were attended by 4 or more women, and only 3 sessions (7.1%) included 3 participants. Very few clients made regular use of the support groups. Only 4 clients (8.5%) participated in more than 3 group sessions. Our findings suggest that teleconferencing may not be the most effective method for providing support services to chemically-dependent women.     

Advances in positron emission tomographic imaging of lung cancer

Positron emission tomography (PET) with [18F]fluorodeoxyglucose (FDG) has been established as a useful tool in the management of patients with non-small cell lung cancer and promises to be as valuable in the clinical management of other cancers. PET imaging with FDG allows the assessment of tumor glucose metabolism in vivo; however, a number of other PET tracers are being used in oncologic research to assess changes in other cellular processes associated with malignant transformation of the cell. [11C]-Labeled methionine and choline are being used to assess changes in cell membrane synthesis; however, small studies have not shown the added information from these tracers to be clinically useful. DNA synthesis can be assessed by measuring the uptake of the thymidine analog 3'-deoxy-3'-[18F]fluorothymidine, which may be more specific for evaluating malignancy without the problem of false-positive results from inflammatory lesions, as seen with FDG. Tumor hypoxia imaging with copper-labeled diacetyl-bis(N(4)-methylthiosemicarbazone) or [18F]fluoromisonidazole may provide a better method of predicting which tumors will respond best to conventional therapy. The role of PET will continue to evolve with further clinical studies using these and other new tracers.     

Simulated environment is not appropriate

In the Spring 2005 issue of Quality Management in Health Care, Borckand et al examined the performance of Tukey's chart in a simulated environment. Unfortunately, the simulated environment does not reflect the type of settings where Tukey's chart has been proposed to be most effective. Tukey's charts are ideally used on relatively small data sets. In these data sets, we hypothesize that it is unlikely to have the high autocorrelations simulated in the Borckand et al study. Furthermore, Tukey's chart will perform well in data coming from non-Normal or non-Uniform distributions. The simulation study was based on random numbers generated with Uniform or Normal distributions. We encourage Borckand et al to examine the performance of Tukey's chart in the modified circumstances.     

Evaluation of Real-Time Tissue Sono-elastography in the Assessment of 214 Breast Lesions: Limitations of This Method Resulting from Different Histologic Subtypes,Tumor Size and Tumor Localization

Real-time sono-elastography is an ultrasound-based technique used to estimate tissue elasticity. Several publications have reported that this method has the ability to differentiate between malignant and benign breast lesions. However, on the basis of current literature, sono-elastography returned false-negative results in 25% of cases with certain lesions, such as mucinous carcinoma. Our data indicate that elastography has higher specificity (96.5% vs. 84.4%) and lower sensitivity (86.9% vs. 93.9%) than B-mode ultrasound. Our evidence suggests that elastography performs significantly worse in lesions ≥20 mm in diameter (sensitivity = 61.1%, specificity = 97.2%) than in lesions <20 mm in diameter (sensitivity = 92.6%, specificity = 96.2%). Furthermore, elastography returned false-negative results in all cases mucinous carcinoma. Finally, in eight cases we obtained a valid elastogram. Our data indicate that this finding is probably due to tumor depth.     

Using observed sequence to orient causal networks

In learning causal networks, typically cross-sectional data are used and the sequence among the network nodes is learned through conditional independence. Sequence is inherently a longitudinal concept. We propose to learn sequence of events in longitudinal data and use it to orient arc directions in a network learned from cross-sectional data. The network is learned from cross-sectional data using various established algorithms, with one modification. Arc directions that do not agree with the longitudinal sequence were prohibited. We established longitudinal sequence through two methods: Probabilistic Contrast, and Goodman and Kruskal error reduction methods. In simulated data, the error reduction method was used to learn the sequence in the data. The procedure reduced the number of arc direction errors and larger improvements were observed with increasing number of events in the network. In real data, different algorithms were used to learn the network from cross-sectional data, while prohibiting arc directions not supported by longitudinal information. The agreement among learned networks increased significantly. It is possible to combine sequence information learned from longitudinal data with algorithms organized for learning network models from cross-sectional data. Such models may have additional causal interpretation as they more explicitly take into account observed sequence of events.     

A psychological approach to learning causal networks

We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks by prohibiting the direction that is less predictive. The heuristic increased predictive accuracy by an average of 0.51 % percent, a small amount. It also increased total agreement between different network learning algorithms (Max Spanning Tree, Taboo, EQ, SopLeq, and Taboo Order) by 25 %. Prior to use of the heuristic, the multiple raters Kappa between the algorithms was 0.60 (95 % confidence interval, CI, from 0.53 to 0.67) indicating moderate agreement among the networks learned through different algorithms. After the use of the heuristic, the multiple raters Kappa was 0.85 (95 % CI from 0.78 to 0.92). There was a statistically significant increase in agreement between the five algorithms (alpha <?0.05). These data suggest that the heuristic increased agreement between networks learned through use of different algorithms, without loss of predictive accuracy. Additional research is needed to see if findings persist in other data sets and to explain why a heuristic used by humans could improve construct validity of mathematical algorithms.