A practical nomogram for predicting cancer-specific survival in patients with clear-cell renal cell carcinoma

Abstract Background: It has limitations in predicting patient cancer-specific survival to use of the traditional American Joint Committee on Cancer (AJCC) staging system alone. Objectives: We aimed to establish and evaluate a comprehensive prognostic nomogram and compare its prognostic value with the AJCC-7th staging system in adults diagnosed with ccRCC.Methods: We used the SEER database to identify 24477 cases of ccRCC between 2010 and 2015. In the development cohort, we used multivariate Cox proportional-hazards analyses to select significant variables, and used R software to establish a nomogram for predicting the 3-year and 5-year cancer-specific survival rates of ccRCC patients. In the development and validation cohorts, we compared our cancer-specific survival model with the AJCC-7th prognosis model to evaluate the performance of the nomogram by calculating the concordance index (C-index), Youden Index, area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI), and performing calibration plotting and decision curve analyses (DCAs). Results: Eleven identified independent prognostic factors were used to establish the nomogram. Age at diagnosis, being unmarried, higher grades, larger tumor size, higher AJCC-7th stage, lymph node metastases, bone metastases, liver metastases, lung metastases, radiotherapy, and no surgery were risk factors for the cancer-specific survival of ccRCC. The C-index, Youden Index, AUC, NRI, IDI, and calibration plots demonstrated the good performance of the nomogram compared to the AJCC-7th staging system. Moreover, the 3-year and 5-year DCA curves showed that the nomogram yielded net benefits that were greater than the traditional AJCC-7th staging system. Conclusion: This study is the first to indicate that married status is an important prognostic parameter in ccRCC. Our results also demonstrate that the developed nomogram can predict cancer-specific survival more accurately than the AJCC-7th staging system alone. The prognostic factors were easily obtained.

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A practical nomogram for predicting cancer-specific survival in patients with clear-cell renal cell carcinoma

10.21203/rs.2.24343/v1 ◽

2020 ◽

Author(s):

Qian Wen ◽

Xinwen Wang ◽

Xiaoye Wang ◽

Tiao Bai ◽

Mei Tao

Keyword(s):

Prognostic Factors ◽

Lung Metastases ◽

Characteristic Curve ◽

Staging System ◽

Cox Proportional Hazards ◽

Cell Renal Cell Carcinoma ◽

Cancer Specific Survival ◽

Net Reclassification Improvement ◽

Ajcc Staging System ◽

Ajcc Staging

Abstract Background: It has limitations in predicting patient survival to use of the traditional American Joint Committee on Cancer (AJCC) staging system alone.Objectives: We aimed to establish and evaluate a comprehensive prognostic nomogram and compare its prognostic value with the AJCC staging system in adults diagnosed with ccRCC.Patients and Methods: We used the SEER database to identify 24477 cases of ccRCC between 2010 and 2015. The patients were randomly divided into two groups. In the development cohort, we used multivariate Cox proportional-hazards analyses to select significant variables, and used R software to establish a nomogram for predicting the 3-year and 5-year survival rates of ccRCC patients. In the development and validation cohorts, we compared our survival model with the AJCC prognosis model to evaluate the performance of the nomogram by calculating the concordance index (C-index), area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI), and performing calibration plotting and decision curve analyses (DCAs). Results: Eleven identified independent prognostic factors were used to establish the nomogram. Age at diagnosis, being unmarried, higher grades, larger tumor size, higher AJCC stage, lymph node metastases, bone metastases, liver metastases, lung metastases, radiotherapy, and no surgery were risk factors for the survival of ccRCC. The C-index, AUC, NRI, IDI, and calibration plots demonstrated the good performance of the nomogram compared to the AJCC staging system. Moreover, the 3-year and 5-year DCA curves showed that the nomogram yielded net benefits that were greater than the traditional AJCC staging system.Conclusion: This study is the first to indicate that married status is an important prognostic parameter in ccRCC. Our results also demonstrate that the developed nomogram can predict survival more accurately than the AJCC staging system alone. The prognostic factors were easily obtained.

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Comparison of prognostic factors and survival outcome between gastrointestinal tract and cutaneous invasive malignant melanoma.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.4_suppl.618 ◽

2012 ◽

Vol 30 (4_suppl) ◽

pp. 618-618

Author(s):

Chi Lin ◽

Christopher K Brown ◽

Charles Arthur Enke ◽

Fausto R. Loberiza

Keyword(s):

Prognostic Factors ◽

Proportional Hazards ◽

Early Stage ◽

Female Gender ◽

Cox Proportional Hazards ◽

Lymph Node Status ◽

Cancer Specific Survival ◽

White Race ◽

Factors Associated ◽

Cox Analysis

618 Background: Gastrointestinal melanoma (GIM) is a rare disease. The objective of this study is to compare the overall survival (OS), cancer specific survival (CSS) and prognostic factors of GIM to those of skin melanoma (SKM) using the Surveillance, Epidemiology, and End Results (SEER) registry. Methods: Patients diagnosed with invasive GIM (406) and SKM (173,622) between 1973 and 2008 were identified from the SEER database. Factors analyzed included age (18-40/41-60/61-100), gender, race (White/nonwhite), marital status, stage (localized/regional/distant), year of diagnosis (1973-87/1988-97/1998-2008), and type of treatment (radiotherapy (RT)/surgery). OS and CSS were evaluated using the Kaplan-Meier method. Cox proportional hazards regression analysis examined what factors were prognostic of survival. Results: The median age was 69 and 57 for patients with GIM and SKM, respectively. The GIM group was older with more advanced-stage cancer than the SKM group. Surgery was performed on 85% and 95%, while RT was received by 18% and 2% of GIM and SKM patients, respectively. The GIM group had a median OS and CSS of 15 and 16 months, respectively, while the SKM group had a median OS of 283 months and did not reach a median CSS. Cox analysis showed that SKM had significantly lower risk of total and cancer-specific mortality compared to GIM (Hazard Ratio (HR) 0.40, p<0.0001) and (HR 0.34, p<0.0001). Factors associated with improved OS and CSS in SKM included: age ≤60, female gender, non-white race, early stage, being married, more recent diagnosis, undergoing surgery and not receiving RT. Factors associated with improved OS and CSS in GIM included: age ≤60, early stage, non-white race and undergoing surgery. Subgroup analysis on patients who underwent surgery showed that lymph node status was the only prognostic factor for GIM, while all of the previously identified prognostic factors except for race were associated with OS and CSS for SKM. Conclusions: Outcomes of patients with GIM are inferior to those with SKM. The melanomas in these two sites also have different prognostic factors. Future studies should explore the reasons behind these differences to improve treatment outcomes.

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A convenient clinical nomogram for predicting the cancer-specific survival of individual patients with small-intestine adenocarcinoma

10.21203/rs.2.21096/v1 ◽

2020 ◽

Author(s):

Na Wang ◽

Jin Yang ◽

Jun Lyu ◽

Qingqing Liu ◽

Hairong He ◽

...

Keyword(s):

Small Intestine ◽

Cox Regression ◽

Characteristic Curve ◽

Survival Rates ◽

Discrimination Performance ◽

Staging System ◽

Tnm Staging ◽

Superior Performance ◽

Cancer Specific Survival ◽

Net Reclassification Improvement

Abstract Background: The objective of this study was to develop a practical nomogram for predicting the cancer-specific survival (CSS) of patients with small-intestine adenocarcinoma. Methods: Patients diagnosed with small-intestine adenocarcinoma. between 2010 and 2015 were selected for inclusion in this study from the Surveillance, Epidemiology, and End Results (SEER) database. The selected patients were randomly divided intothe training and validation cohorts at a ratio of 7:3.The predictors of CSS were identified by applying both forward and backward stepwise selection methods in a Cox regression model. The performance of the nomogram was measured by the concordance index (C-index), the area under receiver operating characteristic curve (AUC), calibration plots, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and decision-curve analysis (DCA). Results: Multivariate Cox regression indicated that factors including age at diagnosis, sex, marital status, insurance status, histology grade, SEER stage, surgery status, T stage, and N stage were independent covariates associated with CSS. These factors were used to construct a predictive model, which was built and virtualized by a nomogram. The C-index of the constructed nomogram was 0.858. The AUC values indicated that the established nomogram displayed better discrimination performance than did the seventh edition of the American Joint Committee on Cancer TNM staging system in predicting CSS. The IDI and NRI also showed that the nomogram exhibited superior performance in both the training and validation cohorts. Furthermore, the calibrated nomogram predicted survival rates that closely corresponded to actual survival rates, while the DCA demonstrated the considerable clinical usefulness of the nomogram. Conclusion: We have constructed a nomogram for predicting the CSS of small-intestine adenocarcinoma patients. This prognostic model may improve the ability of clinicians to predict survival in individual patients and provide them with treatment recommendations.

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A convenient clinical nomogram for predicting the cancer-specific survival of individual patients with small-intestine adenocarcinoma

10.21203/rs.2.21096/v2 ◽

2020 ◽

Author(s):

Na Wang ◽

Jin Yang ◽

Jun Lyu ◽

Qingqing Liu ◽

Hairong He ◽

...

Keyword(s):

Small Intestine ◽

Cox Regression ◽

Characteristic Curve ◽

Survival Rates ◽

Discrimination Performance ◽

Staging System ◽

Tnm Staging ◽

Superior Performance ◽

Cancer Specific Survival ◽

Net Reclassification Improvement

Abstract Background: The objective of this study was to develop a practical nomogram for predicting the cancer-specific survival (CSS) of patients with small-intestine adenocarcinoma . Methods: Patients diagnosed with small-intestine adenocarcinoma between 2010 and 2015 were selected for inclusion in this study from the Surveillance, Epidemiology, and End Results (SEER) database. The selected patients were randomly divided into the training and validation cohorts at a ratio of 7:3. The predictors of CSS were identified by applying both forward and backward stepwise selection methods in a Cox regression model . The performance of the nomogram was measured by the concordance index (C-index), the area under receiver operating characteristic curve (AUC) , calibration plots, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI) , and decision-curve analysis (DCA). Results: Multivariate Cox regression indicated that factors including age at diagnosis, sex, marital status, insurance status, histology grade, SEER stage, surgery status, T stage, and N stage were independent covariates associated with CSS. These factors were used to construct a predictive model, which was built and virtualized by a nomogram. The C-index of the constructed nomogram was 0.850. The AUC values indicated that the established nomogram displayed better discrimination performance than did the seventh edition of the American Joint Committee on Cancer TNM staging system in predicting CSS. The IDI and NRI also showed that the nomogram exhibited superior performance in both the training and validation cohorts. Furthermore, the calibrated nomogram predicted survival rates that closely corresponded to actual survival rates, while the DCA demonstrated the considerable clinical usefulness of the nomogram. Conclusion: We have constructed a nomogram for predicting the CSS of small-intestine adenocarcinoma patients . This prognostic model may improve the ability of clinicians to predict survival in individual patients and provide them with treatment recommendations.

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A convenient clinical nomogram for predicting the cancer-specific survival of individual patients with small-intestine adenocarcinoma

10.21203/rs.2.21096/v3 ◽

2020 ◽

Author(s):

Na Wang ◽

Jin Yang ◽

Jun Lyu ◽

Qingqing Liu ◽

Hairong He ◽

...

Keyword(s):

Small Intestine ◽

Cox Regression ◽

Characteristic Curve ◽

Survival Rates ◽

Discrimination Performance ◽

Staging System ◽

Tnm Staging ◽

Superior Performance ◽

Cancer Specific Survival ◽

Net Reclassification Improvement

Abstract Background: The objective of this study was to develop a practical nomogram for predicting the cancer-specific survival (CSS) of patients with small-intestine adenocarcinoma. Methods: Patients diagnosed with small-intestine adenocarcinoma between 2010 and 2015 were selected for inclusion in this study from the Surveillance, Epidemiology, and End Results (SEER) database. The selected patients were randomly divided into the training and validation cohorts at a ratio of 7:3. The predictors of CSS were identified by applying both forward and backward stepwise selection methods in a Cox regression model. The performance of the nomogram was measured by the concordance index (C-index), the area under receiver operating characteristic curve (AUC), calibration plots, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and decision-curve analysis (DCA).Results: Multivariate Cox regression indicated that factors including age at diagnosis, sex, marital status, insurance status, histology grade, SEER stage, surgery status, T stage, and N stage were independent covariates associated with CSS. These factors were used to construct a predictive model, which was built and virtualized by a nomogram. The C-index of the constructed nomogram was 0.850. The AUC values indicated that the established nomogram displayed better discrimination performance than did the seventh edition of the American Joint Committee on Cancer TNM staging system in predicting CSS. The IDI and NRI also showed that the nomogram exhibited superior performance in both the training and validation cohorts. Furthermore, the calibrated nomogram predicted survival rates that closely corresponded to actual survival rates, while the DCA demonstrated the considerable clinical usefulness of the nomogram.Conclusion: We have constructed a nomogram for predicting the CSS of small-intestine adenocarcinoma patients. This prognostic model may improve the ability of clinicians to predict survival in individual patients and provide them with treatment recommendations.

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A comparison of published multidimensional indices to predict outcome in idiopathic pulmonary fibrosis

ERJ Open Research ◽

10.1183/23120541.00096-2016 ◽

2017 ◽

Vol 3 (1) ◽

pp. 00096-2016 ◽

Cited By ~ 10

Author(s):

Charles Sharp ◽

Huzaifa I. Adamali ◽

Ann B. Millar

Keyword(s):

Prognostic Factors ◽

Idiopathic Pulmonary Fibrosis ◽

Pulmonary Fibrosis ◽

Exercise Testing ◽

Proportional Hazards ◽

Characteristic Curve ◽

Cox Proportional Hazards ◽

Pulmonary Physiology ◽

Multidimensional Indices ◽

The Uk

Idiopathic pulmonary fibrosis (IPF) has an unpredictable course and prognostic factors are incompletely understood. We aimed to identify prognostic factors, including multidimensional indices from a significant IPF cohort at the Bristol Interstitial Lung Disease Centre in the UK.Patients diagnosed with IPF between 2007 and 2014 were identified. Longitudinal pulmonary physiology and exercise testing results were collated, with all-cause mortality used as the primary outcome. Factors influencing overall, 12- and 24-month survival were identified using Cox proportional hazards modelling and receiver operating characteristic curve analysis.We found in this real-world cohort of 167 patients, diffusing capacity for carbon monoxide (DLCO) and initiation of long-term oxygen were independent markers of poor prognosis. Exercise testing results predicted 12-month mortality as well as DLCO, but did not perform as well for overall survival. The Composite Physiological Index was the best performing multidimensional index, but did not outperform DLCO. Our data confirmed that patients who experienced a fall in forced vital capacity (FVC) >10% had significantly worse survival after that point (p=0.024).Our data from longitudinal follow-up in IPF show that DLCO is the best individual prognostic marker, outperforming FVC. Exercise testing is important in predicting early poor outcome. Regular and complete review should be conducted to ensure appropriate care is delivered in a timely fashion.

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Nomogram to predict the prognosis of parotid gland mucoepidermoid carcinoma: a population-based study of 1306 cases

PeerJ ◽

10.7717/peerj.7237 ◽

2019 ◽

Vol 7 ◽

pp. e7237

Author(s):

Jian Sun ◽

Yang Sun ◽

Fei Yang ◽

Qianrong Zhou ◽

Wenjuan Liu ◽

...

Keyword(s):

Prognostic Factors ◽

Parotid Gland ◽

Mucoepidermoid Carcinoma ◽

Proportional Hazards ◽

Population Based ◽

Cox Proportional Hazards ◽

Individual Characteristics ◽

Rank Test ◽

Cancer Specific Survival ◽

Salivary Gland Malignancy

Background Mucoepidermoid carcinoma (MEC) is a common cancer in the oral salivary gland malignancy, which mainly occurs in the parotid gland. The aim of this study is to identify independent prognostic factors and establish a nomogram model for parotid gland mucoepidermoid carcinoma (P-MEC) patients using the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database. Method Patients with P-MEC were selected from between 2004 and 2015. The overall survival (OS) and cancer-specific survival (CSS) rates were estimated using the Kaplan-Meier method with the log-rank test. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify the independent prognostic factors. Results A total of 1,306 patients with P-MEC were enrolled. Age, grade, T stage, N stage, M stage, chemotherapy, and surgery type were independent prognostic factors for OS and CSS. A nomogram for OS was formulated based on these independent prognostic factors and validated using an internal bootstrap resampling approach, which showed that the nomogram exhibited a sufficient level of discrimination according to the C-index (0.877, 95% CI [0.855–0.898]). Conclusion Several prognostic factors for P-MEC were identified. The nomogram developed in this study accurately predicted the 5- and 10-year OS rates of American patients with P-MEC based on individual characteristics. Risk stratification using the survival nomogram can optimize individual therapies and follow-up.

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Real-World Implications of Nonbiological Factors with Staging, Prognosis and Clinical Management in Colon Cancer

Cancers ◽

10.3390/cancers10080263 ◽

2018 ◽

Vol 10 (8) ◽

pp. 263 ◽

Cited By ~ 2

Author(s):

Qi Liu ◽

Dakui Luo ◽

Sanjun Cai ◽

Qingguo Li ◽

Xinxiang Li

Keyword(s):

Colon Cancer ◽

Proportional Hazards ◽

Staging System ◽

Tnm Staging ◽

Cox Proportional Hazards ◽

Metastatic Colon Cancer ◽

Cancer Specific Survival ◽

Increased Risk ◽

Tnm Staging System ◽

Risk Of Cancer

Background: The present study analyzed the nonbiological factors (NBFs) together with the American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) staging system to generate a refined, risk-adapted stage for the clinical treatment of colon cancer. Methods: Eligible patients (N = 28,818) with colon cancer between 1 January 2010 and 31 December 2014, were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier curves and Cox proportional hazards regression, analyzed the probabilities of cancer-specific survival (CSS) in patients with colon cancer, with different NBF-TNM stages. Results: Insurance status, marital status, and median household income were significant prognostic NBFs in the current study (p < 0.05). The concordance index of NBF-TNM stage was 0.857 (95% confidence interval (CI) = 0.8472–0.8668). Multivariate Cox analyses, indicated that NBF1-stage was independently associated with a 50.4% increased risk of cancer-specific mortality in colon cancer (p < 0.001), which increased to 77.1% in non-metastatic colon cancer. NBF0-stage improved in CSS as compared to the NBF1-stage in the respective stages (p < 0.05). Conclusions: The new proposed NBF-stage was an independent prognostic factor in colon cancer. Effect of NBFs on the survival of colon cancer necessitates further clinical attention. Moreover, the incorporation of NBF-stage into the AJCC TNM staging system is essential for prognostic prediction, and clinical guidance of adjuvant chemotherapy in stage II and III colon cancer.

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Proliferation-dominant high-grade astrocytoma: survival benefit associated with extensive resection of FLAIR abnormality region

Journal of Neurosurgery ◽

10.3171/2018.12.jns182775 ◽

2020 ◽

Vol 132 (4) ◽

pp. 998-1005 ◽

Cited By ~ 4

Author(s):

Haihui Jiang ◽

Yong Cui ◽

Xiang Liu ◽

Xiaohui Ren ◽

Mingxiao Li ◽

...

Keyword(s):

Survival Benefit ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Characteristic Curve ◽

Extent Of Resection ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Model ◽

High Grade ◽

Extensive Resection ◽

High Grade Astrocytoma

OBJECTIVEThe aim of this study was to investigate the relationship between extent of resection (EOR) and survival in terms of clinical, molecular, and radiological factors in high-grade astrocytoma (HGA).METHODSClinical and radiological data from 585 cases of molecularly defined HGA were reviewed. In each case, the EOR was evaluated twice: once according to contrast-enhanced T1-weighted images (CE-T1WI) and once according to fluid attenuated inversion recovery (FLAIR) images. The ratio of the volume of the region of abnormality in CE-T1WI to that in FLAIR images (VFLAIR/VCE-T1WI) was calculated and a receiver operating characteristic curve was used to determine the optimal cutoff value for that ratio. Univariate and multivariate analyses were performed to identify the prognostic value of each factor.RESULTSBoth the EOR evaluated from CE-T1WI and the EOR evaluated from FLAIR could divide the whole cohort into 4 subgroups with different survival outcomes (p < 0.001). Cases were stratified into 2 subtypes based on VFLAIR/VCE-T1WIwith a cutoff of 10: a proliferation-dominant subtype and a diffusion-dominant subtype. Kaplan-Meier analysis showed a significant survival advantage for the proliferation-dominant subtype (p < 0.0001). The prognostic implication has been further confirmed in the Cox proportional hazards model (HR 1.105, 95% CI 1.078–1.134, p < 0.0001). The survival of patients with proliferation-dominant HGA was significantly prolonged in association with extensive resection of the FLAIR abnormality region beyond contrast-enhancing tumor (p = 0.03), while no survival benefit was observed in association with the extensive resection in the diffusion-dominant subtype (p=0.86).CONCLUSIONSVFLAIR/VCE-T1WIis an important classifier that could divide the HGA into 2 subtypes with distinct invasive features. Patients with proliferation-dominant HGA can benefit from extensive resection of the FLAIR abnormality region, which provides the theoretical basis for a personalized resection strategy.

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7 Prognostic factors for overall survival in patients with advanced melanoma treated with Anti-PD-1 therapy – the melimmune score

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0007 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A7-A7

Author(s):

Soraia Lobo-Martins ◽

Diogo Martins-Branco ◽

Patrícia Miguel Semedo ◽

Cecília Melo Alvim ◽

Ana Maria Monteiro ◽

...

Keyword(s):

Risk Factors ◽

Prognostic Factors ◽

Poor Prognosis ◽

Proportional Hazards ◽

Checkpoint Inhibitors ◽

Prognostic Score ◽

Daily Practice ◽

Cox Proportional Hazards ◽

Time To Death ◽

Line Setting

BackgroundImmune checkpoint inhibitors (ICI) have changed the paradigm of advanced malignant melanoma (MM). Several prognostic factors, mostly linked to inflammation, have been under scope to better select patients for such therapies. We aimed to build and apply a prognostic score in this setting.MethodsBaseline characteristics and outcomes on 147 patients with advanced MM treated with an anti-PD1 (nivolumab or pembrolizumab) in monotherapy, between Jan-2016 and Oct-2019, in the 1st, 2nd or 3rd line setting were collected from two centres in Portugal. Data cut-off for follow-up was May-2020. Cox proportional hazards regression was used to identify independent prognostic factors for OS.ResultsWith a median FU of 28.93 months (95% CI [22.52–33.54]), mOS for the whole cohort was 14.75 months (95% CI, [10.80–18.71]). Overall, 43 and 104 patients were treated with nivolumab and pembrolizumab, respectively. We identified four adverse prognostic factors that were independent predictors of bad prognosis: number of metastatic sites >2 (p<0.001), baseline PS-ECOG =1 (p<0.001), presence of baseline lymphopenia (over lower limit of normal) (p=0.002) or very high baseline LDH (>2x upper limit of normal) (p<0.001).Patients were separated into three risk categories according to the number of risk factors present: favourable prognosis (no risk factors; n=34), intermediate prognosis (one risk factor; n=65) and poor prognosis (two or more risk factors; n=48). mOS was 43.41 (95% CI [32.13–54.69], 14.39 (95% CI [6.78–22.01]) and 6.53 months (95% CI [3.61–9.44]), for favourable, intermediate, and poor prognosis group, respectively (p<0.001; figure 1). AUC of ROC curve for OS was 0.737 (95% CI [0.654–0.819], p<0.001).Abstract 7 Figure 1Time to death - Kaplan-Meier survival plotConclusionsUsing easily accessible parameters from our daily practice, we propose the MELImmune prognostic score for advanced MM patients treated with anti-PD1 in monotherapy that could be incorporated to the daily clinical practice and clinical trials. We further aim to validate this score in an independent larger sample.Ethics ApprovalThe study was approved by both institutions’ Ethics Committee.

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