13 research outputs found
Novel prognostic factors for advanced melanoma and localized renal cell carcinoma
This study aimed to evaluate prognostic and predictive factors in melanoma and renal cell carcinoma to tailor optimal treatment and follow-up for cancer patients.
Chemotherapy was the standard treatment for advanced melanoma before immune checkpoint inhibitors and targeted therapies. The median overall survival was 8.9 months (95% CI 7.5–10.4) and the five-year survival rate 13% in 146 patients who had received BOLD-IFN chemoimmunotherapy at Turku University Hospital in 1991─2010. Long-term survivors were found especially in patients without visceral metastases (five-year survival rate 28%).
The Finnish Melanoma Group conducted a prospective, multicenter trial enrolling 38 patients who received TOL-IFN (temozolomide, lomustine, vincristine, and interferone-alpha) ± vemurafenib for the first-line treatment of advanced cutaneous melanoma. Elevated LDH was associated with shorter overall survival unlike asymptomatic brain metastases. Undetectable circulating tumor DNA in baseline plasma samples correlated with longer progression-free survival and baseline ctDNA levels were inversely associated with overall survival. Patients with persistent detectable ctDNA during treatment had the shortest overall survival.
One-third of patients will develop disease recurrence after surgery for localized renal cell carcinoma. Tumor size, tumor grade (Fuhrman), and microvascular invasion were sufficient for the accurate prediction of metastasis-free survival in 196 patients operated for localized clear cell RCC. The three-feature prediction model was validated in an external cohort of 714 patients. It retained similar prediction accuracy as the Leibovich model (C-index 0.836 vs. 0.848, p=0.106) and had better prognostic value for long-term prediction in both cohorts
In conclusion, undetectable ctDNA is a novel biomarker indicating favourable prognosis in advanced melanoma. This study suggests that patients with persistent detectable ctDNA may require more frequent monitoring of treatment response and perhaps more intensive therapy. We also introduced a three-feature prediction model for metastasis-free survival as a tool for optimizing postoperative follow-up of localized RCC patients.Edenneen melanooman ja paikallisen munuaissyövän uudet ennustetekijät
Tämän väitöskirjatutkimuksen tavoitteena oli löytää uusia ennustetekijöitä, jotka voivat auttaa suunnittelemaan melanooma- ja munuaissyöpäpotilaiden yksilöllistä hoitoa ja seurantaa.
Ensimmäisessä osatyössä tutkittiin solunsalpaajahoidon ja alfainterferonin (DOBC-IFN) hyötyä ennustavia tekijöitä. 146 potilasta oli saanut DOBC-IFN-hoitoa TYKS:ssä edenneen ihomelanooman vuoksi vuosina 1991–2010. Potilaiden eliniän mediaani oli 8,9 kuukautta (95 prosentin luottamusväli 7,5–10,4 kk) ja viiden vuoden kohdalla elossa olevien potilaiden osuus oli 13 prosenttia. Jopa 28 prosenttia potilaista, joilla ei ollut todettu sisäelinetäpesäkkeitä, pysyi elossa viisi vuotta.
Toisessa ja kolmannessa osatyössä raportoitiin tulokset Suomen Melanoomaryhmän toteuttamasta prospektiivisesta kansallisesta monikeskustutkimuksesta, jossa annettiin 38:lle edennyttä ihomelanoomaa sairastavalle potilaalle solunsalpaajien, alfainterferonin (TOL-IFN) ja vemurafenibin yhdistelmähoitoa. Korkea plasman laktaattidehydrogenaasipitoisuus ennusti lyhyempää elinaikaa, kun taas oireettomat aivometastaasit eivät olleet yhteydessä lyhyempään elinaikaan. Veressä kiertävä kasvain-DNA ennusti nopeampaa taudin etenemistä ja kasvain- DNA:n määrä oli kääntäen verrannollinen elinajan pituuteen. Lyhyin elinaika todettiin potilailla, joilla kasvain-DNA ei hävinnyt hoidon aikana toistetusti otetuista plasmanäytteistä.
Neljännessä osatyössä osoitettiin, että syöpäkasvaimen koko, syöpäsolujen erilaistumisaste ja leviäminen hiusverisuoniin ennustavat luotettavasti etäpesäkkeiden ilmaantumista paikallisen kirkassoluisen munuaissyövän leikkauksen jälkeen.
Johtopäätöksenä voidaan todeta, että veressä kiertävä kasvain-DNA ennustaa melanoomapotilaiden elinaikaa. Mikäli kiertävä kasvain-DNA ei häviä hoidon aikana, voidaan harkita hoidon tehostamista. Neljännessä osatyössä esitellyn uuden nomogrammin avulla voidaan arvioida potilaan riskiä sairastua levinneeseen munuaissyöpään ja tätä luokittelua voidaan käyttää, kun suunnitellaan potilaan seurantaa paikallisen kirkassoluisen munuaissyövän leikkauksen jälkeen
A three-feature prediction model for metastasis-free survival after surgery of localized clear cell renal cell carcinoma
After surgery of localized renal cell carcinoma, over 20% of the patients will develop distant metastases. Our aim was to develop an easy-to-use prognostic model for predicting metastasis-free survival after radical or partial nephrectomy of localized clear cell RCC. Model training was performed on 196 patients. Right-censored metastasis-free survival was analysed using LASSO-regularized Cox regression, which identified three key prediction features. The model was validated in an external cohort of 714 patients. 55 (28%) and 134 (19%) patients developed distant metastases during the median postoperative follow-up of 6.3 years (interquartile range 3.4-8.6) and 5.4 years (4.0-7.6) in the training and validation cohort, respectively. Patients were stratified into clinically meaningful risk categories using only three features: tumor size, tumor grade and microvascular invasion, and a representative nomogram and a visual prediction surface were constructed using these features in Cox proportional hazards model. Concordance indices in the training and validation cohorts were 0.755 +/- 0.029 and 0.836 +/- 0.015 for our novel model, which were comparable to the C-indices of the original Leibovich prediction model (0.734 +/- 0.035 and 0.848 +/- 0.017, respectively). Thus, the presented model retains high accuracy while requiring only three features that are routinely collected and widely available.Peer reviewe
A three-feature prediction model for metastasis-free survival after surgery of localized clear cell renal cell carcinoma
After surgery of localized renal cell carcinoma, over 20% of the patients will develop distant metastases. Our aim was to develop an easy-to-use prognostic model for predicting metastasis-free survival after radical or partial nephrectomy of localized clear cell RCC. Model training was performed on 196 patients. Right-censored metastasis-free survival was analysed using LASSO-regularized Cox regression, which identified three key prediction features. The model was validated in an external cohort of 714 patients. 55 (28%) and 134 (19%) patients developed distant metastases during the median postoperative follow-up of 6.3 years (interquartile range 3.4-8.6) and 5.4 years (4.0-7.6) in the training and validation cohort, respectively. Patients were stratified into clinically meaningful risk categories using only three features: tumor size, tumor grade and microvascular invasion, and a representative nomogram and a visual prediction surface were constructed using these features in Cox proportional hazards model. Concordance indices in the training and validation cohorts were 0.755 +/- 0.029 and 0.836 +/- 0.015 for our novel model, which were comparable to the C-indices of the original Leibovich prediction model (0.734 +/- 0.035 and 0.848 +/- 0.017, respectively). Thus, the presented model retains high accuracy while requiring only three features that are routinely collected and widely available
Impact of morning stiffness on working behaviour and performance in people with rheumatoid arthritis
Prognostic Factors for Localized Clear Cell Renal Cell Carcinoma and Their Application in Adjuvant Therapy
Approximately 20% of patients with renal cell carcinoma (RCC) present with primarily metastatic disease and over 30% of patients with localized RCC will develop distant metastases later, after complete resection of the primary tumor. Accurate postoperative prognostic models are essential for designing personalized surveillance programs, as well as for designing adjuvant therapy and trials. Several clinical and histopathological prognostic factors have been identified and adopted into prognostic algorithms to assess the individual risk for disease recurrence after radical or partial nephrectomy. However, the prediction accuracy of current prognostic models has been studied in retrospective patient cohorts and the optimal set of prognostic features remains unclear. In addition to traditional histopathological prognostic factors, novel biomarkers, such as gene expression profiles and circulating tumor DNA, are extensively studied to supplement existing prognostic algorithms to improve their prediction accuracy. Here, we aim to give an overview of existing prognostic features and prediction models for localized postoperative clear cell RCC and discuss their role in the adjuvant therapy trials. The results of ongoing placebo-controlled adjuvant therapy trials may elucidate prognostic factors and biomarkers that help to define patients at high risk for disease recurrence
Prognostic Factors for Localized Clear Cell Renal Cell Carcinoma and Their Application in Adjuvant Therapy
Approximately 20% of patients with renal cell carcinoma (RCC) present with primarily metastatic disease and over 30% of patients with localized RCC will develop distant metastases later, after complete resection of the primary tumor. Accurate postoperative prognostic models are essential for designing personalized surveillance programs, as well as for designing adjuvant therapy and trials. Several clinical and histopathological prognostic factors have been identified and adopted into prognostic algorithms to assess the individual risk for disease recurrence after radical or partial nephrectomy. However, the prediction accuracy of current prognostic models has been studied in retrospective patient cohorts and the optimal set of prognostic features remains unclear. In addition to traditional histopathological prognostic factors, novel biomarkers, such as gene expression profiles and circulating tumor DNA, are extensively studied to supplement existing prognostic algorithms to improve their prediction accuracy. Here, we aim to give an overview of existing prognostic features and prediction models for localized postoperative clear cell RCC and discuss their role in the adjuvant therapy trials. The results of ongoing placebo-controlled adjuvant therapy trials may elucidate prognostic factors and biomarkers that help to define patients at high risk for disease recurrence
Reasons for Treatment Discontinuation and Their Effect on Outcomes of Immunotherapy in Southwest Finland: A Retrospective, Real-World Cohort Study
Immune checkpoint inhibitors (ICI) have improved survival in several cancer types. Still, most patients develop disease progression during or after treatment. We evaluated the reasons for treatment discontinuation and their effect on treatment outcomes in adult patients with advanced cancer with ICI in the first or later treatment lines in Southwest Finland between 1 January 2015 and 31 December 2021. Baseline characteristics and treatment outcomes were retrospectively obtained from the electronic medical records. There were 317 patients with 15 different cancer types, most commonly non-small cell lung cancer, melanoma, and kidney cancer, treated with ICI outside clinical trials. During follow-up, 94% of the patients had discontinued treatment. A total of 62% was due to disease progression, 17% due to immune-related adverse events (irAEs), 12% after achieving disease control or radiological response, and 9% due to poor performance status. The median progression-free survival (mPFS) was 5.4 months and the median overall survival (mOS) was 20.3 months in the whole cohort. Longer mPFS and mOS were observed in patients who discontinued ICI due to irAEs (24.3 and 49.2 months) and after disease control (49.7 months and not reached). In total, 46% of the patients who discontinued ICI after irAEs or disease control remained alive and progression-free during follow-up
Observational study on the evolution of systemic treatments for advanced renal cell carcinoma in Southwest Finland between 2010 and 2021
Background: Novel receptor tyrosine kinase inhibitors and immune checkpoint inhibitors have been introduced to the treatment of advanced renal cell carcinoma (aRCC) during the past decade. However, the adoption of novel treatments into clinical practice has been unknown in Finland. Objectives: Our aim was to evaluate the use of systemic treatments and treatment outcomes of aRCC patients in Southwest Finland during 2010–2021. Design and Methods: Clinical characteristics, treatments for aRCC, healthcare resource utilization, and overall survival (OS) were retrospectively obtained from electronic medical records. Patients were stratified using the International Metastatic RCC Database Consortium (IMDC) risk classification. Results: In total, 1112 RCC patients were identified, 336 (30%) patients presented with aRCC, and 57% of them ( n = 191) had received systemic treatment. Pre-2018, sunitinib (79%) was the most common first-line treatment, and pazopanib (17%), axitinib (17%), and cabozantinib (5%) were frequently used in the second-line. Post-2018, sunitinib (52%), cabozantinib (31%), and the combination of ipilimumab and nivolumab (10%) were most commonly used in the first-line, and cabozantinib (23%) in the second-line. Median OS for patients with favorable, intermediate, and poor risk were 61.9, 28.6, and 8.1 months, respectively. A total of 73%, 74%, and 35% of the patients with favorable, intermediate, and poor risk had received second-line systemic treatment. In poor-risk patients, the number of hospital inpatient days was twofold higher compared to intermediate and fourfold higher compared to favorable-risk patients. Conclusion: New treatment options were readily adopted into routine clinical practice after becoming reimbursed in Finland. OS and the need for hospitalization depended significantly on the IMDC risk category. Upfront combination treatments are warranted for poor-risk patients as the proportion of patients receiving second-line treatment is low. Registration: Clinical trial identifier: ClinicalTrials.gov NCT05363072