Download ugo de giorgi sii gynecol - v 25 giugno 2015

Studio retrospettivo sulla correlazione tra fattori
biologici immunologici e outcome nelle pazienti
con tumori ginecologici
Ugo De Giorgi
Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori
(I.R.S.T.) IRCCS Meldola
Title of the Systemic immune-inflammation index (SII),
ratio
(PLR)
and
project: Platelet/lymphocyte
Neutrophyls/lymphocyte ratio (NLR) as
prognostic/predictive factors in gynecological
cancers
Research Prognostic factors in gynecological cancers
line:
Principal
Ugo De Giorgi, Medical Oncology
Investigator
Address and e- Medical Oncology IRST-IRCCS, Via Maroncelli 47014 Meldola;
mail:
[email protected]
Participating
centres:
Centres from MITO group
Cancer and inflammation
Cancer and inflammation are strictly linked and cancer patients present local and systemic
modifications in inflammatory parameters as the neutrophyl/lymphocyte ratio (NLR), in
erythrocyte sedimentation rate, in the level of serum inflammatory cytokines, and acutephase proteins, as well as observed in infectious or inflammatory diseases.1-3
Platelets can induce circulating tumor cell epithelial-mesenchymal transition and promote
extravasation to metastatic sites. 4,5
Neutrophyls can promote adhesion and seeding of distant organ sites through secretion of
circulating growth factors such as VEGF and proteases. 6,7
Lymphocytes play a crucial role in tumor defense by inducing cytotoxic cell death and
inhibiting tumor cell proliferation and migration, thereby dictating the host immune response
to malignancy.8
References
1.
2.
3.
4.
5.
6.
7.
8.
Balkwill F, Mantovani A. Cancer and inflammation: implications for pharmacology and therapeutics. Clin Pharmacol Ther. 2010 Apr;87(4):401-6
Gabay C, Acute-phase proteins and other systemic responses to inflammation. New Engl J Medi1999;340(6):448–54
Guthrie GJ, Charlesb KA, Roxburgha CS, Horgana PG, McMillana DC, Clarkec SJ. The systemic inflammation-based neutrophil–lymphocyte ratio: Experience in patients with cancer. Crit Rev Oncol Hematol.
2013 ;88(1):218-30
Labelle M, Begum S, Hynes RO. Direct signaling btween platelets and cancer cells induces epithelial-mesenchymal-like transition and promote metastasis. Cancer Cell 2011; 20:576-590.
Schumacher D, Strilic B, Sivaraj KK, et al. Platelet-derived nucleotides promote tumor-cell transendothelial migration and metastasis via P2Y2 receptor. Cancer Cell 2013;24:130-137.
Cools-Lartigue J, Spicer J, McDonald B, et al. Neutrophyl extracellular traps sequester circulating tumor cells and promote metastasis. J Clin Invest 2013; 123:3446-58.
Rossi L, Santoni M, Crabb SJ, Scarpi E, Burattini L, Chau C, Bianchi E, Savini A, Burgio SL, Conti A, Conteduca V, Cascinu S, De Giorgi. U. High Neutrophil-to-lymphocyte Ratio Persistent During First-line
Chemotherapy Predicts Poor Clinical Outcome in Patients with Advanced Urothelial Cancer. Ann Surg Oncol. 2014 Sep 19. [Epub ahead of print]
De Giorgi U, Mego M, Scarpi E, Giuliano M, Giordano A, Reuben JM, Valero V, Ueno NT, Hortobagyi GN, Cristofanilli M. Relationship between lymphocytopenia and circulating tumor cells as prognostic
factors for overall survival in metastatic breast cancer. Clin Breast Cancer 2012;12(4):264-9.
x-tile 3.6.1 software (Yale University, New Haven, CT)
internet - free
Rationale – Aims
Therefore, inflammation induces cancer microenvironment and systemic
changes that are favorable for cancer progression.
The low cost, easy determination, and reproducibility of a full blood count
make SII, PLR and NLR promising tools as prognostic-predictive factors in
gynecological cancers (GC) including ovarian cancer (OC), endometrial
cancer (EC), cervical cancer (CC).
In this analysis, we aim to evaluate prognostic and predictive implications
of SII, PLR and NLR levels and changes associated and establish a novel risk
stratification model in patients with advanced GC receiving chemotherapy
+/- other agents.
Motivated by these data and other biological data from literature a new
prospective biomarker study will be defined in GC.
Objectives
To evaluate prognostic and predictive implications of SII,
PLR, NLR levels and changes associated and establish a
novel risk stratification model in patients with advanced
GC receiving chemotherapy +/- other agents.
Primary objective correlations with OS and PFS
Secondary objective correlations with ORR, safety,
histotypes, CA125.
Study design (1)
We will review retrospectively medical charts of patients with advanced GC patients treated
with first-line chemotherapy and/or other drugs in our institutions:
- from January 2005 (?) to September 2014 for EC and CC (minimum FU of 10-12 months)
- from January 2011 (?) to September 2014 for OC (beva era & minimum FU of 10-12 mo)
Databases will be separated according to the primary tumors (OC, EC, CC) and clinical setting
(first-line, second-line) to have specific subset analyses, as follows:
-first-line CC,
-first-line EC,
- first-line OC, A specific sub-study on SII, PLR and NLR in OC treated with or without
bevacizumab in first-line setting will be performed focusing on patients with stage III-IV OC
and/or macroscopic residual disease at debulking surgery.
- second line OC, sharing between patients with platinum sensitive/refractory disease
Exclusion criteria will include:
- < 1month from treatment use of steroids or other systemic antineoplastic therapy
- <1 month from treatment or during the first cycle of CT onset of infection known to be
associated with a change of blood counts.
- G-CSF use within 1 week from the 2nd cycle
Study design (2)
The optimal cut-off values of SII, PLR and NLR will be evaluated in every disease (OC, EC, CC)
and setting during the respective analysis of data.
The cut-offs will be evaluated at baseline (pre-therapy) and at day 1 of the second cycle
(follow-up).
The accuracy of all of the pathologic, clinical, and radiologic data retrieved from the
respective institutional databases will be validated for each patient by an independent
observer using the medical chart.
Data will be entered into electronic data files by the local investigators at each centre and
checked at the central data management for missing information and internal consistency.
Because of the retrospective nature of this analysis, we will not able to perform an intent-totreat analysis and will assess only actual treatments that patients received. Toxicity will be
assessed and registered according to the National Cancer Institute Common Toxicity Criteria
version 3.0 (NCI-CTC v.3.0). The response will be assessed by the treating physician according
to the Response Evaluation Criteria in Solid Tumours (RECIST) criteria on the basis of the
official reports obtained from the medical charts. According to our Institutional procedures,
patients were evaluated at each cycle for safety with clinical visit and full blood examinations
including a complete blood count, whereas a CT scan was done at baseline and repeated
every 3 cycles and at the end of chemotherapy.
Statistical considerations
Data will be summarized by frequency for categorical variables and by median and range for
continuous variables. Association between categorical variables will be assessed using the
Fisher’s exact test, when appropriate. Differences will be considered statistically significant
when P <.05. Progression-free survival (PFS) will be calculated from the start of
chemotherapy until disease progression or last follow-up. Patients who died without
progression were censored at the time of death. Overall survival (OS) will be calculated from
the start of chemotherapy until death. Patients lost to follow-up were censored at the time
of last contact. The Kaplan-Meier method will be used to estimate PFS and OS. The log-rank
test and Cox proportional hazards regression will be used to test for differences between
groups. After univariate analysis, a multivariate analysis will be carried out by Cox regression
model and including all variables of interest for the specific tumor and clinical setting.
We will also conduct landmark analyses to reduce possible confounding by time on
treatment by assessing the impact of change in SII, PLR and NLR at various landmark times
on survival outcomes. Patients with early disease progression/deaths or patients lost to
follow-up before the landmark times will be excluded. For this analysis, PFS and OS times will
be measured from the landmark times to these survival outcomes. The landmark times at 1
and 2 months after the first cycle of chemotherapy will be explored.
Estimated hazard ratios (HR), their 95% CIs and P values will be calculated from the Cox
proportional hazard regression models.
GRAZIE!
IRCCS Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (I.R.S.T.),
Meldola
Gruppo Uro-ginecologico
Ugo De Giorgi
Luca Burgio
Cinzia Conteduca
Cristian Lolli
Cecilia Menna
Giuseppe Schepisi
Emanuela Bianchi (sede Cesena)
Lorena Rossi (specializzanda)