Minimizing postoperative narcotic medications may reduce the risk of developing POUR after laparoscopic inguinal hernia repairs. If possible surgeons should consider non-steroidal anti-inflammatory drugs, acetaminophen, or regional anesthetic blocks to minimize postoperative narcotic requirements.
In patients with significant left ventricular dysfunction and congestive heart failure despite optimal medical therapy, implantation of cardiac resynchronization therapy-defibrillation (CRT-D) devices has been shown to improve symptoms and mortality. In this report, we describe a case of a patient with ischaemic cardiomyopathy who developed incessant ventricular tachycardia (VT) after undergoing an upgrade from an implantable cardioverter defibrillator to a CRT-D device. The patient required multiple anti-arrhythmic agents, removal of the coronary sinus lead, and radiofrequency ablation to control VT. Thus, in rare patients, the CRT devices may potentially cause 'proarrhythmia' with serious consequences.
The TNM staging system is universally used for classification of cancer. This system is limited since it uses only three factors (tumor size, extent of spread to lymph nodes, and status of distant metastasis) to generate stage groups. To provide a more accurate description of cancer and thus better patient care, additional factors or variables should be used to classify cancer. In this paper we propose a hierarchical clustering algorithm to develop prognostic systems that classify cancer according to multiple prognostic factors. This algorithm has many potential applications in augmenting the data currently obtained in a staging system by allowing more prognostic factors to be incorporated. The algorithm clusters combinations of prognostic factors that are formed using categories of factors. The dissimilarity between two combinations is determined by the area between two corresponding survival curves. Groups from cutting the dendrogram and survival curves of the individual groups define our prognostic systems that classify patients using survival outcomes. A demonstration of the proposed algorithm is given for patients with breast cancer from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute.
Background: To visualize the anatomy as revealed by dendrograms of the tumor, lymph node, and metastasis (TNM) staging system for colon cancer and compare it with the Dukes' system. Methods: A hierarchical clustering algorithm generated tree-structured dendrograms that stratified patients according to survival only. The dendrograms were constructed with the same prognostic variables used for the TNM. Because combinations of prognostic factors were stratified only on survival, additional factors of any number and type could be integrated into the TNM without changing the TNM categories. Results: The algorithm provided a step-by-step visualization of the TNM and the Dukes' system for colon cancer. Dendrograms and associated 5-year survival rates were generated for the T category only, the N category only, the T, N combination, and combinations of the T, N, and M, and the T, N, M with histological grade. Dendrograms revealed visual differences between the structure of TNM and the Dukes' system of staging. Dendrograms also revealed how variations in prognostic factors changed survival. By cutting dendrograms along their dissimilarity axis, multiple prognostic subgroups could be created for colon cancer that may reflect outcomes that are more accurate to estimate.Conclusions: Dendrograms provide a new way to view cancer patient staging. They reveal a visual stepby-step hierarchical relationship between survival rates and combinations of prognostic variables. The dendrograms also revealed fundamental differences between the TNM and the Dukes system of staging. By stratifying on survival only, additional factors including molecular factors can be added to the TNM, because it classifies patients according to survival rates only and not according to pre-set rules of prognostic factors and stage groups. The clinical implications of stratifying only survival are discussed.
Background The TNM staging system is a standard classification for recording extent of disease in breast cancer. However, with progress in understanding tumor biology, it is unknown how new prognostic factors that will eventually be integrated with the TNM will affect its predictive ability. Our objective was to show the impact on 10-year survival rates for breast cancer as different combinations of prognostic factors are integrated into the TNM. Methods: Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute for the years 1991 through 2000. After exclusions, 132,339 cases of female breast cancer were available. An ensemble clustering algorithm was used to calculate survival after including additional prognostic factors listed in SEER in the TNM. Combinations of the following 6 factors were sequentially added to the TNM: tumor grade, ER/PR status, age at diagnosis, racial/ethnic group, and histological tumor type. Results: Survival rates amongst some tumors with the same TNM stage varied as new factors were integrated into the TNM. Factors associated with favorable outcome usually were associated with better survival than factors associated with less favorable outcome for each stage group with varying degrees. There were 4 different tumor combinations that represented 4 different TNM stages that all corresponded to a 90% 10-year survival when additional factors were added to the TNM stage. Integration of additional prognostic factors led to a crossover in survival of some stage groups. In one combination (T1, N2, grade 1, ER+, PR+, age <50: 131111) patients who were assigned stage IIIA had a 10-year rate of 90%, which qualifies for a stage I category. Survival Crossover in TNM Staging10-year Survival (%)Prognostic Factor CombinationTNM StageNumber of Patients90113IA1899390112222IA22469021211IIA510190122112IIA40199031111IIB68290131111IIIA82582232221IIB11035822322213IIB92583331111IIIA1285814211111IIIC64**Abbreviated table. Prognostic Factor Combination in order from left to right: T, N, grade, ER status, PR status, age, race, histological type. * T1 = 1; T2 = 2; T3 = 3; N0 = 1; N1= 2; N2 = 3; N3 = 4; Grade 1 = 1; Grade 2 = 2; Grade 3 = 3; ER+ = 1; ER- = 2; PR+ = 1; PR- = 2; Age <= 50 = 1; Age >50 = 2; Conclusions: Integrating new prognostic factors into the TNM always changed the outcome. Survival rates, therefore, are relative and depend on the selection of prognostic factors. Adding new factors selected different cohorts from the population which had a heterogeneous population of cancer survivors. These cohorts usually had different survival rates compared with the overall population from which they were drawn. Integrating combinations of prognostic factors revealed frequent crossover of stage groups at 10 years, which is a violation of a staging system and could impact the interpretation of clinical trials. Citation Format: Jigar A Patel, Matthew T Hueman, Dechang Chen, Donald E Henson. Deconstructing the TNM staging system for breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-08-15.
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