A prospective study on tumour response assessment methods after neoadjuvant endocrine therapy in early oestrogen receptor-positive breast cancer.

BACKGROUND: Neoadjuvant endocrine therapy (NET) in oestrogen receptor-positive (ER+) /HER2-negative (HER2-) breast cancer allows real-time evaluation of drug efficacy as well as investigation of the biological and molecular changes that occur after estrogenic deprivation. Clinical and pathological evaluation after NET may be used to obtain prognostic and predictive information of tumour response to decide adjuvant treatment. In this setting, clinical scales developed to evaluate response after neoadjuvant chemotherapy are not useful and there are not validated biomarkers to assess response to NET beyond Ki67 levels and preoperative endocrine prognostic index score (mPEPI). METHODS: In this prospective study, we extensively analysed radiological (by ultrasound scan (USS) and magnetic resonance imaging (MRI)) and pathological tumour response of 104 postmenopausal patients with ER+ /HER2- resectable breast cancer, treated with NET for a mean of 7 months prior to surgery. We defined a new score, tumour cellularity size (TCS), calculated as the product of the residual tumour cellularity in the surgical specimen and the tumour pathological size. RESULTS: Our results show that radiological evaluation of response to NET by both USS and MRI underestimates pathological tumour size (path-TS). Tumour size [mean (range); mm] was: path-TS 20 (0-80); radiological-TS by USS 9 (0-31); by MRI: 12 (0-60). Nevertheless, they support the use of MRI over USS to clinically assess radiological tumour response (rad-TR) due to the statistically significant association of rad-TR by MRI, but not USS, with Ki67 decrease (p = 0.002 and p = 0.3, respectively) and mPEPI score (p = 0.002 and p = 0.6, respectively). In addition, we propose that TCS could become a new tool to standardize response assessment to NET given its simplicity, reproducibility and its good correlation with existing biomarkers (such as ΔKi67, p = 0.001) and potential added value. CONCLUSION: Our findings shed light on the dynamics of tumour response to NET, challenge the paradigm of the ability of NET to decrease surgical volume and point to the utility of the TCS to quantify the scattered tumour response usually produced by endocrine therapy. In the future, these results should be validated in independent cohorts with associated survival data.

Prognosis stratification of cancer patients treated with immune checkpoint inhibitors through lung immune prognostic index: a meta-analysis and systematic review.

BACKGROUND: Although numerous studies have reported the prognostic value of the lung immune prognostic index (LIPI) in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), the prognostic value of the LIPI in a pancancer setting remains unclear. METHODS: A comprehensive search was conducted until July 2023 across the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant studies evaluating the prognostic value of the LIPI in cancer patients treated with ICIs. The outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). We described and compared the pooled outcomes by stratifying the patients based on different groupings of LIPI (good vs. intermediate [0 vs. 1], good vs. poor [0 vs. 2], and good vs. intermediate / poor [0 vs. 1 + 2]). RESULTS: A total of 9959 patients in 35 studies were included. A higher score of LIPI was associated with impaired OS. The pooled HRs were 1.69 (95% CI: 1.55-1.85, p < 0.001; 0 vs. 1), 3.03 (95% CI: 2.53-3.63, p < 0.001; 0 vs. 2), and 2.38 (95% CI: 1.97-2.88, p < 0.001; 0 vs. 1 + 2). A higher LIPI score was associated with shorter PFS. The pooled HRs were 1.41 (95% CI: 1.31-1.52, p < 0.001; 0 vs. 1), 2.23 (95% CI: 1.87-2.66, p < 0.001; 0 vs. 2), and 1.65 (95% CI: 1.46-1.86, p < 0.001; 0 vs. 1 + 2). Similarly, a higher LIPI score was associated with a lower ORR. The pooled ORs were 0.63 (95% CI: 0.54-0.75, p < 0.001; 0 vs. 1) and 0.38 (95% CI: 0.29-0.50, p < 0.001; 0 vs. 2). A higher LIPI score was associated with a lower DCR. The pooled ORs were 0.47 (95% CI: 0.35-0.61, p < 0.001; 0 vs. 1) and 0.19 (95% CI: 0.12-0.30, p < 0.001; 0 vs. 2). CONCLUSION: In patients with NSCLC or other solid tumours, the lung immune prognostic index could robustly stratify the clinical outcomes into three groups among the patients who receive ICIs. LIPI is a low-cost, simple, accessible, and accurate prognostic tool in a pancancer setting and it may contribute to the evaluation of risk stratification in patients treated with ICIs.

Secondary central nervous system involvement in patients with diffuse large B-cell lymphoma treated with rituximab combined CHOP therapy - a supplementary analysis of JCOG0601.

Secondary central nervous system involvement (sCNSi) in diffuse large B-cell lymphoma (DLBCL) is fatal. However, its features in patients with sCNSi who are categorized as lower risk by international prognostic index (IPI) or CNS-IPI are not yet fully understood. In the present analysis, we evaluated DLBCL patients who developed sCNSi at their first progression and who participated in JCOG0601, most of whom were lower risk by IPI. Of 409 patients, 21 (5.1%) developed sCNSi during a median follow-up of 4.9 years. Five-year cumulative incidence of sCNSi were 5.1%; and 4.0%, 5.3%, and 11.5% at low, intermediate, and high risk of CNS-IPI, respectively. The most common locations of extranodal lesions at the time of registration in patients with sCNSi were the stomach (n = 4), paranasal cavity (n = 3), and bone marrow (n = 2). In univariable analysis, paranasal cavity lesion was a high-risk factor for sCNSi (subdistribution hazard ratio, 4.34 [95% confidence interval 1.28-14.73]). Median overall survival after sCNSi was 1.3 years, with a 2-year overall survival rate of 39.3%. The incidence of sCNSi in DLBCL patients at lower risk of CNS-IPI was low, as previously reported, but paranasal cavity lesion might indicate high risk for organ involvement. CLINICAL TRIAL REGISTRATION: JCOG0601 was registered in the UMIN Clinical Trials Registry (UMIN000000929, date of registration; December 04, 2007) and the Japan Registry of Clinical Trials (jRCTs031180139, date of registration; February 20, 2019).

An artificial intelligence-driven predictive model for pediatric allogeneic hematopoietic stem cell transplantation using clinical variables.

BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is a procedure with high morbidity and mortality. Identifying patients for maximum benefit and risk assessment is crucial in the decision-making process. This has led to the development of predictive risk models for HSCT in adults, which have limitations when applied to pediatric population. Our goal was to develop an automatic learning algorithm to predict survival in children with malignant disorders undergoing HSCT. METHODS: We studied allogenic HSCTs performed on children with malignant disorders at a third-level hospital between 1991 and 2021. Survival was analyzed using the Kaplan-Meier method, log-rank test for the univariate analysis, and Cox regression for the multivariate analysis. A prognostic index was constructed based on these findings. Lastly, we constructed a predictive model using a random forest algorithm to forecast 1-year survival after HSCT. RESULTS: We analyzed 229 HSCTs in 201 patients with a median follow-up of 1.64 years. Variables that impacted on the multivariate analysis were older age (hazard ratio [HR] 1.40, 95% confidence interval [CI] 1.12-1.76, p = .003), oldest period of HSCT (HR 0.46, 95% CI 0.29-0.73, p < .001), and mismatched donor (HR 2.65, 95% CI 1.51-4.65, p = .001). Our prognostic index was associated with 3-year overall survival (OS; p < .001). A random forest was developed using as variables: diagnosis, age, year of HSCT, time from diagnosis to HSCT, disease stage, donor type, and conditioning. This achieved 72% accuracy in predicting 1-year OS. CONCLUSIONS: Our index and random forest was effective in predicting 1-year survival. However, further validation in diverse populations is necessary to establish their generalizability.

The Italian guideline on comprehensive geriatric assessment (CGA) for the older persons: a collaborative work of 25 Italian Scientific Societies and the National Institute of Health.

BACKGROUND: The guideline was promoted by the Italian General Practitioners-Primary Care and Geriatrics Hospital-Community Societies and was carried out involving the National Institute of Health and an Expert Panel including representatives from 25 Scientific and Health-Professional Organizations. The aim of the Guideline was to develop evidence-based recommendations on the efficacy of CGA in older people across different clinical settings and the accuracy and utility of CGA-based tools to assess prognosis. METHODS: According to the methodological handbook of the Italian National System of Guidelines and NICE criteria (National Institute for Health and Care Excellence in England), the Guideline was produced based on the Grading of Recommendations Assessment, Development and Evaluation. Over 20,000 records gathered through databases searches were initially selected. Sixteen recommendations on CGA efficacy were defined based on 117 studies that met the inclusion criteria and were performed in general practices and primary care (26 studies included), medical and surgical clinics (16 studies), emergency departments (17 studies), hospital medical and surgical wards (53 studies), long-term care facilities and nursing homes (5 studies), hospices and palliative care networks (no studies). Nine recommendations on CGA-based prognostic tools were issues based on 42 included studies carried out in general practices and primary care (5 studies), medical and surgical clinics (4 studies), and hospital wards (33 studies). RESULTS: Using CGA can be useful to reduce hospitalization, mortality, institutionalization, the risk of delirium, and improve appropriateness in drug prescription and maintain functional activities in different settings. Further research on the efficacy of CGA in rehabilitative facilities, nursing homes, and hospice and palliative-care settings is recommended. CGA-based tools, particularly the Multidimensional Prognostic Index, should be used to predict some negative outcomes in different settings. CONCLUSIONS: This Guideline may be useful in clinical practice and as a tool to support research on the use of CGA in older people.

Resilience improvement through a multicomponent physical and cognitive intervention for older people: the DanzArTe emotional well-being technology project.

BACKGROUND: Resilience is a crucial component of successful aging. However, which interventions might increase resilience in older adults is yet unclear. AIMS: This study aims to assess the feasibility and the physical and psychological effects of a technology-based multicomponent dance movement intervention that includes physical, cognitive, and sensory activation in older people living in community-dwelling and nursing home. METHODS: DanzArTe program consists of four sessions on a weekly basis, using a technological platform that integrates visual and auditory contents in real time. 122 participants (mean age = 76.3 ± 8.8 years, 91 females = 74.6%) from seven nursing homes and community-dwelling subjects were assessed, before and after the intervention, with the Resilience Scale-14 items (RES-14), the Multidimensional Prognostic Index (MPI), the Psychological General Well-Being Index (PGWBI-S), and the Client Satisfaction Questionnaire-8 (CSQ-8). Mann-Whitney and Wilcoxon signed-ranks tests were used for statistical analyses. RESULTS: At baseline significant differences in MPI and RES-14 between community-dwelling and nursing home residents were observed (p < 0.001 for both analyses). After the intervention, resilience significantly increased in total sample (RES-14 mean T1 = 74.6 Vs. T2 = 75.7) and in the nursing home residents (RES-14 mean T1 = 68.1 Vs. T2 = 71.8). All participants showed high overall satisfaction for DanzArTe program (CSQ-8 mean = 23.9 ± 4.4). No differences in MPI and PGWBI-S were observed. DISCUSSION: DanzArTe was a feasible intervention and high appreciated by all older adults. Nursing home residents revealed improvements in resilience after DanzArTe program. CONCLUSION: The DanzArTe technology-based multi-component intervention may improve resilience in older people living in nursing homes.

Predictive model for treatment outcomes of peripheral T-cell lymphoma, not otherwise specified, in Taiwanese patients.

PURPOSE: We aimed to explore the clinical outcomes and prognostic factors for PTCL-NOS patients in the real world. METHODS: Clinical data were retrospectively collected from adult patients with PTCL-NOS treated at a single center in Taiwan. RESULTS: 104 PTCL-NOS patients with a median age of 53.0 years were enrolled. Patients with the International Prognostic Index (IPI) or prognostic index for peripheral T-cell lymphoma (PIT) scores of zero had a longer overall survival (OS) and progression free survival (PFS), while patients with IPI or PIT scores ≥1 did poorly. For patients who are eligible for transplantation, the use of pralatrexate as salvage chemotherapy has shown better OS (2-year OS 83.3% vs. 24.4%, P = 0.011) compared to patients who did not. By multivariate analysis, age >60 years, male, B symptoms, ECOG >1, lung involvement, and thrombocytopenia were independent adverse factors for OS. Incorporating factors in multivariate analysis, we established a novel predictive index for PTCL-NOS which efficiently stratifies patients into low (0-1 factor), intermediate-1 (2 factors), intermediate-2 (3 factors), and high risk (4-6 factors) groups with 2-year OS rates of 81.5%, 32.9%, 8.8%, and 0%, respectively (P < 0.001). CONCLUSION: PTCL-NOS patients have a dismal prognosis in Taiwan. Novel agents may improve the outcomes of PTCL-NOS patients. The usefulness of the novel prognostic index for PTCL-NOS needs further validation.

Gene Expression Patterns Associated with Survival in Glioblastoma.

The aim of this study was to investigate gene expression alterations associated with overall survival (OS) in glioblastoma (GBM). Using the Nanostring nCounter platform, we identified four genes (COL1A2, IGFBP3, NGFR, and WIF1) that achieved statistical significance when comparing GBM with non-neoplastic brain tissue. The four genes were included in a multivariate Cox Proportional Hazard model, along with age, extent of resection, and O6-methylguanine-DNA methyltransferase (MGMT) promotor methylation, to create a unique glioblastoma prognostic index (GPI). The GPI score inversely correlated with survival: patient with a high GPI had a median OS of 7.5 months (18-month OS = 9.7%) whereas patients with a low GPI had a median OS of 20.1 months (18-month OS = 54.5%; log rank p-value = 0.004). The GPI score was then validated in 188 GBM patients from The Cancer Genome Atlas (TCGA) from a national data base; similarly, patients with a high GPI had a median OS of 10.5 months (18-month OS = 12.4%) versus 16.9 months (18-month OS = 41.5%) for low GPI (log rank p-value = 0.0003). We conclude that this novel mRNA-based prognostic index could be useful in classifying GBM patients into risk groups and refine prognosis estimates to better inform treatment decisions or stratification into clinical trials.

An N6-methyladenosine regulation- and mRNAsi-related prognostic index reveals the distinct immune microenvironment and immunotherapy responses in lower-grade glioma.

BACKGROUND: N6-methyladenosine (m6A) modification is involved in tumorigenesis and progression as well as closely correlated with stem cell differentiation and pluripotency. Moreover, tumor progression includes the acquisition of stemness characteristics and accumulating loss of differentiation phenotype. Therefore, we integrated m6A modification and stemness indicator mRNAsi to classify patients and predict prognosis for LGG. METHODS: We performed consensus clustering, weighted gene co-expression network analysis, and least absolute shrinkage and selection operator Cox regression analysis to identify an m6A regulation- and mRNAsi-related prognostic index (MRMRPI). Based on this prognostic index, we also explored the differences in immune microenvironments between high- and low-risk populations. Next, immunotherapy responses were also predicted. Moreover, single-cell RNA sequencing data was further used to verify the expression of these genes in MRMRPI. At last, the tumor-promoting and tumor-associated macrophage polarization roles of TIMP1 in LGG were validated by in vitro experiments. RESULTS: Ten genes (DGCR10, CYP2E1, CSMD3, HOXB3, CABP4, AVIL, PTCRA, TIMP1, CLEC18A, and SAMD9) were identified to construct the MRMRPI, which was able to successfully classify patients into high- and low-risk group. Significant differences in prognosis, immune microenvironment, and immunotherapy responses were found between distinct groups. A nomogram integrating the MRMRPI and other prognostic factors were also developed to accurately predict prognosis. Moreover, in vitro experiments illustrated that inhibition of TIMP1 could inhibit the proliferation, migration, and invasion of LGG cells and also inhibit the polarization of tumor-associated macrophages. CONCLUSION: These findings provide novel insights into understanding the interactions of m6A methylation regulation and tumor stemness on LGG development and contribute to guiding more precise immunotherapy strategies.

The relationship between systemic inflammation index, systemic immune-inflammatory index, and inflammatory prognostic index and 90-day outcomes in acute ischemic stroke patients treated with intravenous thrombolysis.

BACKGROUND AND PURPOSE: To explore the association of systemic inflammatory index (SIRI), systemic immune-inflammatory index (SII) and inflammatory prognosis index (IPI) with 90d outcomes in patients with acute ischemic stroke (AIS) after intravenous thrombolysis. METHODS: The patients who underwent intravenous thrombolysis were enrolled in the present study from September 2019 to December 2022. According to the relevant blood indexes obtained in 24 h after admission, the corresponding values of SIRI, SII and IPI were calculated. The correlation among SIRI, SII, IPI, and admission NIHSS scores was examined by Spearman correlation analysis. ROC curve analysis was conducted to determine the optimal cut-off value of SIRI, SII, IPI, and their corresponding sensitivity and specificity to evaluate their predictive value on admission for poor prognosis. To investigate whether high SIRI, SII, and IPI were independent predictors of poor outcomes within 90 days, variables with P-value < 0.05 during univariate analysis were included in multivariate analysis. RESULTS: Compared with the good outcome group, the poor outcome group had higher SIRI, IPI, and SII. Spearman correlation analysis showed that the SIRI, IPI, and SII levels significantly correlated with the admission NIHSS score (r = 0.338, 0.356, 0.427, respectively; Ps < 0.001). Univariate analysis and Multivariate logistic regression analysis revealed high SIRI, SII, and IPI values as independent risk factors for poor 90-day prognosis (OR = 1.09, 1.003 and 7.109, respectively). CONCLUSIONS: High SIRI, IPI, and SII values are correlated with poor 90d outcomes in AIS patients undergoing intravenous thrombolysis.

Characterization and clinical verification of immune-related genes in hepatocellular carcinoma to aid prognosis evaluation and immunotherapy.

BACKGROUND: Immune-related genes (IRGs) have been confirmed to play an important role in tumorigenesis and tumor microenvironment formation in hepatocellular carcinoma (HCC). We investigated how IRGs regulates the HCC immunophenotype and thus affects the prognosis and response to immunotherapy. METHODS: We investigated RNA expression of IRGs and developed an immune-related genes-based prognostic index (IRGPI) in HCC samples. Then, the influence of the IRGPI on the immune microenvironment was comprehensively analysed. RESULTS: According to IRGPI, HCC patients are divided into two immune subtypes. A high IRGPI was characterized by an increased tumor mutation burden (TMB) and a poor prognosis. More CD8 + tumor infiltrating cells and expression of PD-L1 were observed in low IRGPI subtypes. Two immunotherapy cohorts confirmed patients with low IRGPI demonstrated significant therapeutic benefits. Multiplex immunofluorescence staining determined that there were more CD8 + T cells infiltrating into tumor microenvironment in IRGPI-low groups, and the survival time of these patients was longer. CONCLUSIONS: This study demonstrated that the IRGPI serve as a predictive prognostic biomarker and potential indicator for immunotherapy.

The elderly prognostic index predicts early mortality in older patients with diffuse large B-cell lymphoma. An ad hoc analysis of the elderly project by the Fondazione Italiana Linfomi.

The Elderly Prognostic Index (EPI) is based on the integration of a simplified geriatric assessment, hemoglobin levels and International Prognostic Index and has been validated to predict overall survival in older patients with diffuse large B-cell lymphoma (DLBCL). In this study, we evaluated the ability of EPI to predict the risk of early mortality. This study included all patients registered in the Elderly Project for whom treatment details and a minimum follow-up of 3 months were available. Three main treatment groups were identified based on the anthracycline amount administered: cases receiving >70% of the theoretical anthracyclines dose (Full Dose [FD] group), ≤70% (Reduced Dose [RD]) and palliative therapy (PT; no anthracyclines). The primary endpoint was early mortality rate, defined as death for any cause occurring within 90 days from diagnosis. We identified 1150 patients with a median age of 76 years (range 65-94). Overall, 69 early deaths were observed, accounting for 19% of all reported deaths. The cumulative rate of early mortality at 90 days was 6.0%. Comparing early with delayed deaths, we observed a lower frequency of deaths due to lymphoma progression (42% vs. 75%; p < 0.001) and a higher frequency due to toxicity and infections (22% vs. 4%, p < 0.001, and 22% vs. 3%, p < 0.001, respectively) for early events. A multivariable logistic analysis on 931 patients (excluding PT) confirmed an independent association of high-risk EPI (odds ratio [OR] 3.60; 95% confidence interval [CI] 1.15-11.2) and bulky disease (OR 2.08; 95% CI 1.09-3.97) with the risk of early mortality. The cumulative incidence of early mortality for older patients with DLBCL is not negligible and is mainly associated with non-lymphoma related events. For patients receiving anthracyclines, high-risk EPI and bulky disease are associated with a higher probability of early mortality.

A tumor microenvironment-based prognostic index for osteosarcoma.

BACKGROUND: The tumor microenvironment (TME) has a central role in the oncogenesis of osteosarcomas. The composition of the TME is essential for the interaction between tumor and immune cells. The aim of this study was to establish a prognostic index (TMEindex) for osteosarcoma based on the TME, from which estimates about patient survival and individual response to immune checkpoint inhibitor (ICI) therapy can be deduced. METHODS: Based on osteosarcoma samples from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, the ESTIMATE algorithm was used to estimate ImmuneScore and StromalScore. Combined differentially expressed gene analysis, weighted gene co-expression network analyses, the Least Absolute Shrinkage and Selection Operator regression and stepwise regression to construct the TMEindex. The prognostic role of TMEindex was validated in three independent datasets. The molecular and immune characteristics of TMEindex and the impact on immunotherapy were then comprehensively investigated. The expression of TMEindex genes in different cell types and its effects on osteosarcoma cells were explored by scRNA-Seq analysis and molecular biology experiments. RESULTS: Fundamental is the expression of MYC, P4HA1, RAMP1 and TAC4. Patients with high TMEindex had worse overall survival, recurrence-free survival, and metastasis-free survival. TMEindex is an independent prognostic factor in osteosarcoma. TMEindex genes were mainly expressed in malignant cells. The knockdown of MYC and P4HA1 significantly inhibited the proliferation, invasion and migration of osteosarcoma cells. A high TME index is related to the MYC, mTOR, and DNA replication-related pathways. In contrast, a low TME index is related to immune-related signaling pathways such as the inflammatory response. The TMEindex was negatively correlated with ImmuneScore, StromalScore, immune cell infiltration, and various immune-related signature scores. Patients with a higher TMEindex had an immune-cold TME and higher invasiveness. Patients with a low TME index were more likely to respond to ICI therapy and achieve clinical benefit. In addition, the TME index correlated with response to 29 oncologic drugs. CONCLUSIONS: The TMEindex is a promising biomarker to predict the prognosis of patients with osteosarcoma and their response to ICI therapy, and to distinguish the molecular and immune characteristics.

Prognostic significance of absolute monocyte count and lymphocyte to monocyte ratio in mucosa-associated lymphoid tissue (MALT) lymphoma.

To investigate the prognostic significance of peripheral blood absolute monocyte count (AMC) and lymphocyte to monocyte ratio (LMR) in mucosa-associated lymphoid tissue (MALT) lymphoma, we retrospectively analyzed 316 newly diagnosed patients with MALT lymphoma. The best cut-off value of AMC was 0.6 × 109/L and LMR was 1.8 by x-tile according to progression-free survival (PFS). Multivariate analysis showed that MALT-IPI (p < 0.001), Eastern Cooperative Oncology Group performance status (ECOG PS) (p = 0.010), and LMR (p = 0.003) have independent prognostic significance for PFS, MALT-International Prognostic Index (MALT-IPI) (p = 0.018), ß2-microglobulin (ß2-MG) (p = 0.015), and LMR (p = 0.029) predicted poor overall survival (OS). Receiver-operator characteristic (ROC) curves were used to compare the prognostic prediction capability of MALT-IPI and MALT-IPI-M (MALT-IPI combined with LMR); area under the curves (AUCs) for MALT-IPI-M were larger than that for MALT-IPI both PFS (0.682 vs 0.654) and OS (0.804 vs 0.788). Our results indicated that that low level LMR at diagnosis was associated with inferior prognosis. The new prognostic index, MALT-IPI-M, enabled the risk stratification capability for MALT lymphoma survival.

A good preoperative immune prognostic index is precits a better prognosis for locally advanced rectal cancer patients with ypTNM stage II who underwent radical resection after neoadjuvant chemoradiotherapy.

BACKGROUND: No studies have investigated the role of IPI in assessing the prognosis of locally advanced rectal cancer (LARC) patients undergoing nCRT. OBJECTIVE: We attempted to combine neutrophil-to-lymphocyte ratio (NLR) and serum lactate dehydrogenase (sLDH) to generate a new rectal immune prognostic index (RIPI) to explore whether RIPI is associated with LARC prognosis. We aimed to identify whether there is a population that might benefit from RIPI in LARC. METHODS: LARC patients who underwent radical surgery after Neoadjuvant chemoradiotherapy (nCRT) were enrolled between February 2012 and May 2017. Based on the best cut-off points of NLR and sLDH, we developed RIPI. The patients were grouped as follows: (1) good, RIPI = 0, good, 0 factors; (2) poor, RIPI = 1, 1 or 2 factors. RESULTS: This study enrolled 642 patients. In yp TNM stage II patients, 5-year disease-free survival (DFS) differed significantly between the RIPI = 1 and RIPI = 0 groups (p = 0.03). Five-year DFS did not differ significantly between IPI = 0 and IPI = 1 groups in ypCR, stage I, stage II, and stage III. In multivariate analysis, the significant factor predicting DFS was pre-nCRT RIPI score (p = 0.035). CONCLUSION: The pre-nCRT RIPI was closely related to the prognosis of LARC patients undergoing nCRT. Particularly, RIPI is significant in evaluating the prognosis of ypTNM stage II LARC patients who underwent radical resection after nCRT.

Prognostic significance of the systemic inflammation response index in gastrointestinal malignancy patients: a pooled analysis of 10,091 participants.

Background: We performed a meta-analysis to investigate the association of the systemic inflammation response index (SIRI) with long-term survival outcomes in patients with gastrointestinal malignancy. Methods: PubMed, Web of Science and Embase were searched for relevant studies evaluating the prognostic significance of the SIRI in gastrointestinal malignancies until May 2023. Results: 30 studies with 10,091 patients were included. The pooled results identified that patients in the high SIRI group had a worse overall survival and disease-free survival, which was observed across various tumor types, tumor stages and primary treatments. Conclusion: An elevated SIRI is negatively associated with worse survival outcomes of gastrointestinal malignancy patients and can be used as a risk stratification index for gastrointestinal malignancies.

Performance of the Palliative Prognostic Index for cancer patients: A systematic review and meta-analysis.

BACKGROUND: Clinician predicted survival for cancer patients is often inaccurate, and prognostic tools may be helpful, such as the Palliative Prognostic Index (PPI). The PPI development study reported that when PPI score is greater than 6, it predicted survival of less than 3 weeks with a sensitivity of 83% and specificity of 85%. When PPI score is greater than 4, it predicts survival of less than 6 weeks with a sensitivity of 79% and specificity of 77%. However, subsequent PPI validation studies have evaluated various thresholds and survival durations, and it is unclear which is most appropriate for use in clinical practice. With the development of numerous prognostic tools, it is also unclear which is most accurate and feasible for use in multiple care settings. AIM: We evaluated PPI model performance in predicting survival of adult cancer patients based on different thresholds and survival durations and compared it to other prognostic tools. DESIGN: This systematic review and meta-analysis was registered in PROSPERO (CRD42022302679). We calculated the pooled sensitivity and specificity of each threshold using bivariate random-effects meta-analysis and pooled diagnostic odds ratio of each survival duration using hierarchical summary receiver operating characteristic model. Meta-regression and subgroup analysis were used to compare PPI performance with clinician predicted survival and other prognostic tools. Findings which could not be included in meta-analyses were summarised narratively. DATA SOURCES: PubMed, ScienceDirect, Web of Science, CINAHL, ProQuest and Google Scholar were searched for articles published from inception till 7 January 2022. Both retrospective and prospective observational studies evaluating PPI performance in predicting survival of adult cancer patients in any setting were included. The Prediction Model Risk of Bias Assessment Tool was used for quality appraisal. RESULTS: Thirty-nine studies evaluating PPI performance in predicting survival of adult cancer patients were included (n = 19,714 patients). Across meta-analyses of 12 PPI score thresholds and survival durations, we found that PPI was most accurate for predicting survival of <3 weeks and <6 weeks. Survival prediction of <3 weeks was most accurate when PPI score>6 (pooled sensitivity = 0.68, 95% CI 0.60-0.75, specificity = 0.80, 95% CI 0.75-0.85). Survival prediction of <6 weeks was most accurate when PPI score>4 (pooled sensitivity = 0.72, 95% CI 0.65-0.78, specificity = 0.74, 95% CI 0.66-0.80). Comparative meta-analyses found that PPI performed similarly to Delirium-Palliative Prognostic Score and Palliative Prognostic Score in predicting <3-week survival, but less accurately in <30-day survival prediction. However, Delirium-Palliative Prognostic Score and Palliative Prognostic Score only provide <30-day survival probabilities, and it is uncertain how this would be helpful for patients and clinicians. PPI also performed similarly to clinician predicted survival in predicting <30-day survival. However, these findings should be interpreted with caution as limited studies were available for comparative meta-analyses. Risk of bias was high for all studies, mainly due to poor reporting of statistical analyses. while there were low applicability concerns for most (38/39) studies. CONCLUSIONS: PPI score>6 should be used for <3-week survival prediction, and PPI score>4 for <6-week survival. PPI is easily scored and does not require invasive tests, and thus would be easily implemented in multiple care settings. Given the acceptable accuracy of PPI in predicting <3- and <6-week survival and its objective nature, it could be used to cross-check clinician predicted survival especially when clinicians have doubts about their own judgement, or when clinician estimates seem to be less reliable. Future studies should adhere to the reporting guidelines and provide comprehensive analyses of PPI model performance.

Prognostic Impact of Cancer Inflammation Prognostic Index for Non-small Cell Lung Cancer.

PURPOSE: Cancer-inflammation prognostic index (CIPI) is calculated by multiplying the concentration of carcinoembryonic antigen by neutrophil-to-lymphocyte ratio. CIPI has been reported as a prognostic factor for colorectal cancer. Although carcinoembryonic antigen and neutrophil-to-lymphocyte ratio have been reported as prognostic factors for non-small cell lung cancer (NSCLC), it has not been investigated whether CIPI is a useful marker. METHODS: We analyzed the prognostic factors, including CIPI, in 700 NSCLC patients treated by pulmonary resection. We also analyzed a subgroup of 482 patients with pathological stage I NSCLC. RESULT: CIPI > 14.59 (P < 0.01), maximum standardized uptake value (SUVmax) > 5.35 (P < 0.01), lymphatic invasion (P = 0.01), and pathological stage (P < 0.01) were significant factors for relapse-free survival (RFS) in multivariate analysis. SUVmax > 5.35 (P < 0.01) and pathological stage (P < 0.01) were revealed as significant factors for overall survival in the multivariate analysis. In the subanalysis, CIPI > 14.88 (P = 0.01) and SUVmax > 5.07 (P < 0.01) were significant factors for RFS of pathological stage I NSCLC in multivariate analysis. CONCLUSION: CIPI was a significant factor for RFS in NSCLC patients treated surgically, even in those with pathological stage I disease. SUVmax was also a significant factor for RFS and overall survival in NSCLC patients treated surgically, and for RFS in patients with pathological stage I NSCLC. TRIAL REGISTRATION: The Institutional Review Board of Kanazawa Medical University approved the protocol of this retrospective study (Approval Number: I392), and written informed consent was obtained from all patients.

A coordinated strategy for a simple, pragmatic approach to the early identification of the ultra-high-risk patient with diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most frequent aggressive lymphoma seen in clinical practice. Despite huge strides in understanding its biology, front-line therapy has remained unchanged for decades. Roughly one-third of patients have primary refractory or relapse following the end of conventional first-line therapy. The outcome of patients with primary refractory disease and those with early relapse (defined as relapse less than 1 year from the end of therapy) is markedly inferior to those with later relapse and is exemplified by dismal overall survival. In this article, the authors term patients with features that identify them as being at particularly high-risk for either primary refractory disease or early relapse, as 'ultra-high-risk'. As new treatment options become established (e.g. bispecific T-cell engagers, chimeric antigen receptor 'CAR' T-cells and antibody-drug conjugates), it is likely that there will be a push to incorporate some of these agents into the first-line setting for patients identified as ultra-high-risk. In this review, the authors outline advances in positron emission tomography, widely available laboratory assays and clinical prognosticators, which can detect a high proportion of patients with ultra-high-risk disease. Since these approaches are pragmatic and able to be adopted widely, they could be incorporated into routine clinical practice.

The PRO-HOME Project. A multicomponent intervention for the protected discharge from the hospital of multimorbid and polytreated older individuals by using innovative technologies: A pilot study.

BACKGROUD: Discharge planning from the hospital of frail older patients is an important step to avoid inappropriate long-stay hospitalizations and to prevent the risks related to the prolonged hospitalization. In this frame, we developed an experimental trial-'PRO-HOME', a multicomponent programme of interventions for multimorbid and polytreated hospitalized older patients. AIM: The main aim of the study was to develop a protected discharge facility using a mini apartment equipped with advanced architectural and technological components to reduce the length of hospital stay of older participants (aged 65+ years old) admitted to the hospital for an acute event, deemed stable and dischargeable. MATERIALS AND METHODS: This is a pilot randomized controlled study, comparing 30 hospitalized participants included in a multidimensional, transitional care programme based on information and communication technologies to 30 patients in standard usual care until hospital discharge. RESULTS: We presented the study design of the PRO-HOME programme, including architectural and technological components, the enrolment procedures, the components of the intervention that is physical activity, cognitive training and life-style education and the evaluation method of the intervention based on the Comprehensive Geriatric Assessment to explore the changes in the individual domains that are target of the multicomponent intervention. CONCLUSIONS: The final results will suggest whether the PRO-HOME programme represents a useful and feasible intervention to reduce the length of hospital stay of multimorbid and polytreated hospitalized older patients and improve their physical and cognitive performances and overall quality of life. PATIENT OR PUBLIC CONTRIBUTION: Due to the characteristics of the population of interest of the PRO-HOME study, we involved in the study design and programme of the activities the participants enrolled in a previous smart home-based project named MoDiPro carried-out during a 3-year period. The elderly participants from the local population involved were asked, by means of focus groups, for feedback on their experience in MoDiPro, and their suggestions were integrated into the design phase of the current PRO-HOME project. The focus groups included open group interviews with a qualitative collection of the patients' feedback so that the participants could interact with each other.