Meta-analysis of neoadjuvant immunotherapy for non-metastatic colorectal cancer.

Background: Immunotherapy has been approved for the treatment of metastatic colorectal cancer. The efficacy and safety of neoadjuvant immunotherapy for the treatment of non-metastatic colorectal cancer remains unclear. We tried to explore clinical effect of neoadjuvant immunotherapy in the treatment of non-metastatic colorectal cancer. Methods: We searched the databases (PubMed, Wanfang Embase, Cochrane Library and China National Knowledge Infrastructure databases) to obtain suitable articles up to September 2022. The primary outcomes of pathological complete response (pCRs), major pathological response (MPR), objective response rate (ORR), R0-resection and anus preserving rate were collected and evaluated. Secordary outcomes (pCRs and MPR) of subgroup analysis between deficient mismatch repair/microsatellite instability-high group (dMMR/MSI-H) and proficient mismatch repair/microsatellite stable group (pMMR/MSS) and outcomes for rectal cancer were analyzed for the final results. Results: We included ten articles and 410 cases of non-metastatic colorectal cancer with neoadjuvant immunotherapy. There were 113 (27.5%) cases with the dMMR/MSI-H status and 167 (40.7%) cases with the pMMR/MSS status. pCRs was found in 167/373 (44.6%) patients (ES: 0.49, 95% CI: 0.36 to 0.62, P<0.01, chi2 = 65.3, P<0.01, I 2 = 86.2%) and MPR was found in 194/304 (63.8%) patients (ES: 0.66, 95% CI: 0.54 to 0.78, P<0.01, chi2 = 42.55, P<0.01, I 2 = 81.2%) with the random-effects model and huge heterogeneity. In the subgroup analysis, pCRs was higher in the dMMR/MSI-H group than the pMMR/MSS group in the fixed-effects model with minimal heterogeneity (OR: 3.55, 95% CI: 1.74 to 7.27, P<0.01, chi2 = 1.86, P=0.6, I 2 = 0%). pCRs was found in 58/172 (33.9%) rectal cancer patients (ES: 0.33, 95% CI: 0.26 to 0.40, P<0.01, chi2 = 3.04, P=0.55, I 2 = 0%) with the fixed-effects model and little heterogeneity. Conclusion: Neoadjuvant immunotherapy could increase pCRs and MPR rate for non-metastatic colorectal cancer. Neoadjuvant immunotherapy could achieve better pCRs rate in dMMR/MSI-H group than in the pMMR/MSS group. Neoadjuvant immunotherapy could be another treatment option for non-metastatic colorectal cancer. Systematic review registration: https://www.crd.york.ac.uk/prospero/#myprospero, identifier CRD42022350523.

An iterative expanding and shrinking process for processor allocation in mixed-parallel workflow scheduling.

Parallel computation has been widely applied in a variety of large-scale scientific and engineering applications. Many studies indicate that exploiting both task and data parallelisms, i.e. mixed-parallel workflows, to solve large computational problems can get better efficacy compared with either pure task parallelism or pure data parallelism. Scheduling traditional workflows of pure task parallelism on parallel systems has long been known to be an NP-complete problem. Mixed-parallel workflow scheduling has to deal with an additional challenging issue of processor allocation. In this paper, we explore the processor allocation issue in scheduling mixed-parallel workflows of moldable tasks, called M-task, and propose an Iterative Allocation Expanding and Shrinking (IAES) approach. Compared to previous approaches, our IAES has two distinguishing features. The first is allocating more processors to the tasks on allocated critical paths for effectively reducing the makespan of workflow execution. The second is allowing the processor allocation of an M-task to shrink during the iterative procedure, resulting in a more flexible and effective process for finding better allocation. The proposed IAES approach has been evaluated with a series of simulation experiments and compared to several well-known previous methods, including CPR, CPA, MCPA, and MCPA2. The experimental results indicate that our IAES approach outperforms those previous methods significantly in most situations, especially when nodes of the same layer in a workflow might have unequal workloads.