Real-world perspectives on cancer patients receiving immune checkpoint inhibitor therapies

Abstract Progress in the field of immuno-oncology has changed the treatment landscape of cancer. Typically, with PD-(L)1-inhibitors responses are seen in 20–40% of the patients yet most fail to respond. From a clinical perspective, constantly expanding indications together with the high expenses of immune checkpoint inhibitors (ICIs), are challenging, while the optimal length of PD-(L)1-inhibitors remains undetermined. Therefore, predictive biomarkers are needed to guide patient selection. Cancer patients suffer from a variety of symptoms, either derived from the malignancy itself, or as side effects of cancer treatments. Worsening of symptoms indicates cancer progression or severe side-effects and is linked to poorer cancer survival. Web-based applications coupled with an urgency algorithm have been developed to monitor cancer patients. Electronic patient-reported outcomes (ePROs) have been shown to improve quality of life (QoL) and increase the number of patients receiving active cancer treatments at disease progression. Furthermore, the use of ePROs in cancer patient monitoring has shown impressive improvements in overall survival compared to standard follow-up. The toxicity spectrum of ICIs is wide and inadequately characterized. The side effects of ICIs resemble autoimmune disease. These side effects, unlike those of traditional cancer therapies can occur from months to years after therapy initiation or even after therapy discontinuation. Hence, long-term, feasible follow-up of patients is warranted. This present study aims to evaluate the optimal treatment duration of PD-(L)1-inhibitors, to seek predictive factors for therapy selection, and to investigate the feasibility and clinical relevance of ePRO symptom follow-up on cancer patients receiving immune checkpoint inhibitors in real-life.Tiivistelmä Immunologisten syövänhoitojen kehitys on muuttanut erityisesti levinnyttä syöpää sairastavien potilaiden hoitoa. Immuunivasteen tarkastuspisteen estäjiä saavista syöpäpotilaista vain noin 20–40 prosenttia hyötyy hoidosta. On epäselvää, mikä on optimaalinen hoidon kesto ja ketkä hoidosta olettavasti hyötyisivät. Kun käyttöindikaatiot kyseisen ryhmän lääkkeille lisääntyvät kiihtyvällä tahdilla, myös taloudellisesta näkökulmasta katsottuna hoidon tehoa ennakoivien tekijöiden tutkimus on keskeistä. Syöpähoitoja saavat potilaat kärsivät monenlaisista oireista, joista useiden on osoitettu ennustavan huonompaa selviytymistä syövästä. On olemassa useita hälytystoiminnolla varustettuja verkkosovelluksia syöpää sairastavien potilaiden voinnin seuraamiseksi, joiden on osoitettu parantavan oireiden hallintaa, lisäävän potilaiden ja kliinikoiden välistä kommunikaatiota sekä edistävän potilaiden hyvinvointia ja jopa pidentävän elossaoloaikaa perinteiseen seurantaan verrattuna. Immuunivasteen tarkastuspisteen estäjien haittavaikutukset perustuvat samaan mekanismiin kuin hoitojen teho. Immunologisten hoitojen tärkeimmät haitat muistuttavat autoimmuunisairauksia. Hoitoihin liittyy perinteisiä syövän lääkehoitoja laajempi kirjo haittoja, joista tavallisimpia ovat ihottumat, suolisto- ja maksatulehdukset ja endokrinologiset muutokset. Haittojen ilmaantuminen ei ole suorassa ajallisessa yhteydessä lääkkeen antoon, sillä haittoja on raportoitu useiden kuukausien kuluttua lääkityksen aloituksesta sekä lääkityksen tauotuksen jälkeenkin. Pitkäaikainen potilaiden seuranta on siksi keskeistä. Tämän väitöskirjatutkimuksen tavoitteena on arvioida immuunivasteen tarkastuspisteen estäjien optimaalista hoidon kestoa, etsiä hoidon tehoa ennakoivia tekijöitä ja arvioida sähköisen potilaslähtöisen oireseurannan käytettävyyttä ja kliinistä merkitystä immuunivasteen tarkastuspisteen estäjiä saavien syöpäpotilaiden seurannassa

Possibilities of improving the clinical value of immune checkpoint inhibitor therapies in cancer care by optimizing patient selection

Abstract Immune checkpoint inhibitor (ICI) therapies have become the most important medical therapies in many malignancies, such as melanoma, non-small-cell lung cancer, and urogenital cancers. However, due to generally low response rates of PD-(L)1 monotherapy, both PD-(L)1 combination therapies and novel therapeutics are under large-scale clinical evaluation. Thus far, clinical trials have rather suboptimally defined the patient population most likely to benefit from ICI therapy, and there is an unmet need for negative predictive markers aiming to reduce the number of non-responding patients in clinical practice. Furthermore, there is a strong need for basic tumor immunology research and innovative clinical trials to fully unleash the potential of ICI combinations for the benefit of patients

Edenneen ei-pienisoluisen keuhkosyövän lääkehoito:molekyyligenetiikka, täsmälääkkeet ja immuno-onkologia tiennäyttäjinä

Tiivistelmä Valtaosa keuhkosyövistä on ei-pienisoluista keuhkosyöpää. Sen levinneen tautimuodon ennuste on merkittävästi parantunut uusien täsmälääkkeiden ja immuno-onkologisten hoitojen myötä. Ei-pienisoluisen keuhkosyövän hoidon optimaalinen suunnittelu vaatii molekyylipatologisia erityistutkimuksia, joiden edellytys on edustavien kudosnäytteiden otto. Vaikka vain pieni osa potilaista soveltuu täsmälääkehoitoihin, yksittäisen potilaan kannalta aktivoiviin mutaatioihin suunnattujen kohdennettujen hoitojen ennusteellinen merkitys on huomattava. Immuno-onkologisten hoitojen kohdepotilasjoukko on suuri, mutta vain murto-osa heistä hyötyy lääkehoidoista

Association of rare immune-related adverse events to survival in advanced cancer patients treated with immune checkpoint inhibitors:a real-world single-center cohort study

Abstract Immune checkpoint inhibitors (ICIs) are associated with immune-related (ir) adverse events (AEs) resembling autoimmune diseases. In this retrospective cohort study of patients (pts) treated with ICIs at Oulu University Hospital from 2014–2020, we analysed the spectrum of severe irAEs and their prognostic nature, focusing on rare irAEs. Pts (n = 173) with lung cancer (n = 76, 43.9%), melanoma (n = 56, 32.4%), renal and bladder cancers (n = 34, 19.7%), head and neck cancers (n = 4, 2.3%), SCC (n = 2, 1.2%), and CRC (n = 1, 0.6%) receiving single anti-PD-(L)1 (n = 160) or combination (ICI-ICI n = 9, ICI-chemotherapy n = 4) therapy were included. The survival analysis focused on single anti-PD-(L)1-treated patients with melanoma, lung cancer, and renal and bladder cancers (n = 142). Grade ≥ 3 irAEs of multiple aetiology occurred in 29 patients treated with single-PD-L1 therapy (20.4%), which was associated with improved progression-free survival (PFS) (HR 0.50, CI 0.31–0.78) but not overall survival (OS) (HR 0.88, CI 0.52–1.50). Rare grade ≥ 3 events occurred in 10 (7.0%) pts with no association with PFS (HR 0.90, CI 0.42–1.94). Hence, the presence of rare grade ≥ 3 irAEs was associated with a tendency for inferior OS (HR 1.44, CI 0.66–3.11). Pts with rare grade ≥ 3 irAEs had inferior OS, possibly reflecting the delay in diagnostic workflow and the treatment of irAEs. One explanation for the high incidence of irAEs could be the Finnish population-based genetic variation affecting the immune system

Treatment discontinuation and re-initiation of anti-PD-(L)1 agents in metastatic cancers

Abstract Introduction: Immune checkpoint inhibitors (ICIs) are approved in multiple indications for cancer care. Most of the clinical trials have not questioned shorter than until disease progression approaches. In this study, we present results from a cohort of multiple advanced cancers treated with restricted anti-PD-(L)1 therapy. Methods: All patients with advanced cancers treated with anti-PD-(L)1 therapy outside clinical trials at Oulu University Hospital 2014–19 were retrospectively identified from pharmacy records. Clinical variables, treatment history and survival were collected. Results: 106 patients with median age of 66 years with lung cancer (n = 45, 42.5%), melanoma (n = 30, 28.3%), renal and bladder cancers (GU cancers) (n = 26, 24.5%), head and neck (H&N) cancer (n = 4, 3.8%), and colorectal cancer (n = 1, 0.9%) were included in the study. The median (m) OS for the whole population was 14 months (CI 9.7–18.3), 9 months (CI 6.3–11.7) for patients with no IO-free period (n = 64, 62.1%), and 27.0 months (CI 20.6–33.4, p = 0.000001) for patients (n = 39) with IO-free period. The mIO-free survival was 10.0 months (CI 7.1–12.9) for the whole cohort, 8.0 months (CI 1.7–14.3) for lung cancer, 23.0 months (CI 2.6–43.4) for melanoma, and 14.0 months (CI 0.0–20.4) for GU cancer. From the IO-free cohort, 19 patients needed re-treatment during follow-up, of which 8 were re-challenged with anti-PD-(L)1 therapy. The clinical benefit rate of anti-PD-(L)1 re-challenge was 37.5%. Conclusions: Our study shows that long IO-free periods can be achieved with limited duration of anti-PD-(L)1 therapy with excellent survival outcomes, and that anti-PD-(L)1 re-challenge is feasible in clinical practice

Kohdennetut syövän hoidot:häviääkö syöpäkirurgia?

Tiivistelmä Kirurgia on keskeistä kiinteiden kasvainten kuratiivisessa hoidossa mutta tarpeen joskus myös oireiden hoidossa tai diagnostiikassa. Syövän täsmähoitojen nopea kehitys on mahdollistanut entistä tehokkaamman ja siedettävämmän hoidon, ja kokonaan uusia hoitomuotoja on tullut laajamittaiseen käyttöön. Voivatko täsmähoidot vähentää kirurgian merkitystä syövän hoidossa? Nykyisin on käytettävissä vähän laadukkaita tutkimuksia, jotka osoittaisivat täsmähoitojen yhdenvertaisuuden tai paremmuuden syöpäkirurgiaan verrattuna. Olemme kaukana tilanteesta, jossa syövän täsmähoidot syrjäyttäisivät kirurgian aseman parantavana hoitomuotona.Abstract Targeted cancer therapies : is cancer surgery vanishing? Surgery plays a central role in the diagnosis of solid tumors and in curative and sometimes even symptomatic treatment. The rapid progress in targeted treatments for cancer has enabled a more effective and better tolerated treatment, and entirely new therapies have been widely adopted. Can targeted therapies reduce the importance of surgery in the treatment of cancer? There are currently few high-quality studies available that would demonstrate the equality or superiority of targeted therapies over cancer surgery. We are far from a situation where targeted treatments for cancer would displace the role of surgery as a curative treatment

Tetracyclines increase the survival of NSCLC patients treated with EGFR TKIs:a retrospective nationwide registry study

Abstract Background: With the first and second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs), clinical benefit and rash correlate together. EGFR TKI-induced rash can be alleviated with tetracyclines, but it is unknown whether the use of tetracyclines can increase the survival of non-small-cell lung cancer (NSCLC) patients treated with EGFR TKIs. Methods: We collected all the patients (n=1271) who had reimbursement for EGFR TKIs (gefitinib, erlotinib and afatinib) in Finland 2011–2016, had purchased TKIs, and had data available at nationwide cancer registry. The survival was analysed from the first EGFR TKI purchase to death or end-of follow-up, and patients were stratified according to TKIs, purchases of antibiotics, their ATC class and timing. Results: 802 (63.1%) patients had antibiotic purchases −14 to +200 days from the first EGFR TKI purchase, 447 of these tetracyclines. 322 (25.3%) had had purchased antibiotics −14 to +14 days (prophylaxis) from the first EGFR TKI purchase, 188 of these tetracyclines. Purchase of antibiotics was associated with improved survival (HR 0.80, 95% CI 0.71 to 0.91), which limited to tetracycline purchases only (HR 0.72, 95% CI 0.64 to 0.82). The largest survival benefit was seen with the prophylactic use of tetracyclines (HR 0.74, 95% CI 0.62 to 0.88). The benefit from tetracyclines was limited to erlotinib only (HR 0.68, 95% CI 0.58 to 0.78) which was retained in multivariate analysis. Prophylactic use of tetracyclines was associated with a longer erlotinib treatment duration (HR 0.81, 95% CI 0.61 to 0.96) but not with dose reductions or treatment breaks. Conclusions: Tetracyclines improve the survival of NSCLC patients treated with the first and second-generation EGFR TKIs and they should be considered as a prophylaxis when initiating EGFR TKIs with high incidence of rash

Assessment of chemotherapy-induced neurotoxicity using a point-of-care nerve conduction study device

Abstract Background: Management for chemotherapy-induced peripheral neuropathy (CIPN) includes prompt recognition and dose reduction or discontinuation of the neurotoxic agents. CIPN remains under-detected in routine clinical practice and better methods for its early detection are warranted. Aims: To evaluate the feasibility of a point-of-care device in the early detection of CIPN. Methods and Results: Cancer patients (n = 12) scheduled to receive neurotoxic chemotherapy docetaxel, oxaliplatin (OX), or vincristine were recruited for the pilot study (NCT04778878). The patients were assessed with a point-of-care nerve conduction study device (Mediracer® NCS), EORTC QLQ-CIPN20 and NPSI questionnaires, and healthcare professional-assessed CTCAE-based grading at baseline and thereafter every 6-weeks up to 18 weeks or until chemotherapy discontinuation. The set-up of point-of-care device was easy but it only provide successful NCS measurement results in 55% of the patients. The factors related to failed measurement were older age, more frequent comorbidities, and a history of smoking. With the follow-up measurements, decreasing median nerve mean conduction velocity and amplitude, and increasing median nerve mean distal latency were detected on OX-patients. Of the used questionnaires, NPSI was found to be non-feasible with majority of the patients failing to complete the questionnaire while CIPN20 was feasible on all the subjects. CIPN20 score did not show any changes in the follow-up. Conclusions: Point-of-care assessment for NCS was feasible but measurements frequently failed especially on patients with pre-existing high-risk for neuropathy. OX-treated showed decreasing NCS results while other measures were unable to access the change. The system should be further validated with a larger patient cohort preferably treated with OX and low-risk for pre-existing neuropathy

Predicting Objective Response Rate (ORR) in Immune Checkpoint Inhibitor (ICI) Therapies with Machine Learning (ML) by combining clinical and patient-reported data

Abstract ICIs are a standard of care in several malignancies; however, according to overall response rate (ORR), only a subset of eligible patients benefits from ICIs. Thus, an ability to predict ORR could enable more rational use. In this study a ML-based ORR prediction model was built, with patient-reported symptom data and other clinical data as inputs, using the extreme gradient boosting technique (XGBoost). Prediction performance for unseen samples was evaluated using leave-one-out cross-validation (LOOCV), and the performance was evaluated with accuracy, AUC (area under curve), F1 score, and MCC (Matthew’s correlation coefficient). The ORR prediction model had a promising LOOCV performance with all four metrics: accuracy (75%), AUC (0.71), F1 score (0.58), and MCC (0.4). A rather good sensitivity (0.58) and high specificity (0.82) of the model were seen in the confusion matrix for all 63 LOOCV ORR predictions. The two most important symptoms for predicting the ORR were itching and fatigue. The results show that it is possible to predict ORR for patients with multiple advanced cancers undergoing ICI therapies with a ML model combining clinical, routine laboratory, and patient-reported data even with a limited size cohort

Electronic patient-reported outcomes and machine learning in predicting immune-related adverse events of immune checkpoint inhibitor therapies

Abstract Background: Immune-checkpoint inhibitors (ICIs) have introduced novel immune-related adverse events (irAEs), arising from various organ systems without strong timely dependency on therapy dosing. Early detection of irAEs could result in improved toxicity profile and quality of life. Symptom data collected by electronic (e) patient-reported outcomes (PRO) could be used as an input for machine learning (ML) based prediction models for the early detection of irAEs. Methods: The utilized dataset consisted of two data sources. The first dataset consisted of 820 completed symptom questionnaires from 34 ICI treated advanced cancer patients, including 18 monitored symptoms collected using the Kaiku Health digital platform. The second dataset included prospectively collected irAE data, Common Terminology Criteria for Adverse Events (CTCAE) class, and the severity of 26 irAEs. The ML models were built using extreme gradient boosting algorithms. The first model was trained to detect the presence and the second the onset of irAEs. Results: The model trained to predict the presence of irAEs had an excellent performance based on four metrics: accuracy score 0.97, Area Under the Curve (AUC) value 0.99, F1-score 0.94 and Matthew’s correlation coefficient (MCC) 0.92. The prediction of the irAE onset was more difficult with accuracy score 0.96, AUC value 0.93, F1-score 0.66 and MCC 0.64 but the model performance was still at a good level. Conclusion: The current study suggests that ML based prediction models, using ePRO data as an input, can predict the presence and onset of irAEs with a high accuracy, indicating that ePRO follow-up with ML algorithms could facilitate the detection of irAEs in ICI-treated cancer patients. The results should be validated with a larger dataset. Trial registration: Clinical Trials Register (NCT3928938), registration date the 26th of April, 2019