Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration.

Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration. Of 198 samples, 129 represented the discovery phase and 69 represented the validation phase.

Project description:PURPOSE:Use of nonopioid analgesics (including nonsteroidal anti-inflammatory drugs) for postoperative pain management can reduce opioid consumption and potentially prevent opioid-related adverse events. This study examined the postoperative opioid-sparing effect of repeated-dose injectable diclofenac formulated with hydroxypropyl-?-cyclodextrin (HP?CD)-diclofenac. PATIENTS AND METHODS:Pooled data from two double-blind, randomized, placebo- and active comparator-controlled Phase III trials were analyzed. Patients received HP?CD-diclofenac, placebo, or ketorolac by intravenous injection every 6 hours for up to 5 days following abdominal/pelvic or orthopedic surgery. Rescue opioid use was evaluated from the time of first study drug administration to up to 120 hours following the first dose in the overall study population and in subgroups defined by baseline pain severity, age, and HP?CD-diclofenac dose. RESULTS:Overall, 608 patients received ?1 dose of study medication and were included in the analysis. While 93.2% of patients receiving placebo required opioids, the proportion of patients requiring opioids was significantly lower for patients receiving HP?CD-diclofenac (18.75, 37.5, or 50 mg) or ketorolac (P<0.005 for all comparisons). Mean cumulative opioid dose and number of doses were significantly lower among patients receiving HP?CD-diclofenac versus placebo for the 0-24 through 0-120 hour time periods (P<0.0001), as well as versus ketorolac for the 0-72 through 0-120 hour time periods (P<0.05). HP?CD-diclofenac significantly reduced opioid consumption versus placebo in subgroups based on baseline pain severity (moderate, severe) and age (<65 years, ?65 years) from the 0-24 hour period onward. When compared to ketorolac, HP?CD-diclofenac also significantly reduced cumulative opioid consumption among patients with moderate baseline pain (0-72 through 0-120 hours) and opioid dose number among patients ?65 years old (0-24 through 0-120 hours). CONCLUSION:HP?CD-diclofenac can reduce postoperative opioid requirements. As this analysis was not powered to compare opioid-related adverse event rates, follow-up studies examining the clinical impact of HP?CD-diclofenac's opioid sparing are warranted.

Dataset Information

Impact of postoperative complications on the colorectal cancer survival and recurrence: analyses of pooled individual patients' data from three large phase III randomized trials.

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Impact of postoperative complications on the colorectal cancer survival and recurrence: analyses of pooled individual patients' data from three large phase III randomized trials.

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