Intraoperative monitoring study of ipsilateral motor evoked potentials in scoliosis surgery

Ipsilateral motor evoked potentials (MEPs) in spinal cord surgery intraoperative monitoring is not well studied. We show that ipsilateral MEPs have significantly larger amplitudes and were elicited with lower stimulation intensities than contralateral MEPs. The possible underlying mechanisms are discussed based on current knowledge of corticospinal pathways. Ipsilateral MEPs may provide additional information on the integrity of descending motor tracts during spinal surgery monitoring.
Introduction
Intraoperative monitoring (IOM) of the motor pathways is a routine procedure for ensuring integrity of corticospinal tracts during scoliosis surgery. In combination with somatosensory evoked potentials, motor evoked potential (MEP) monitoring is widely utilized in operations with significant risks of spinal cord damage [2, 14].
MEPs are most effectively obtained with multi-pulse cortical electrical stimulation during IOM [3]. However, anesthetic agents, which cause suppression of cortical and spinal motor neuron excitability, affect them [4, 5]. While most IOM protocols involving MEPs utilize total intravenous anesthesia (TIVA), we have previously reported success with desflurane as a halogenated inhalational anesthetic agent [15].
In IOM, MEPs are elicited mostly with contralateral cortical electrical stimulation. Ipsilateral MEP responses have not been adequately studied in this context. Our paper describes observations of ipsilateral and contralateral MEPs with bilateral recordings, in conjunction with TIVA or desflurane during IOM of scoliosis surgery.
Methods
We studied nine patients (mean age 16.2 years; range 14–17 years; 1 male) over a 6-month period in a prospective manner. The local ethical committee has approved the study protocol. All patients did not have medical conditions contraindicating transcranial electrical stimulation. Apart from scoliosis, they were healthy and had normal neurological examinations.
Multi-pulse transcranial electrical stimulation was performed using two constant-current stimulators connected in parallel configuration from a Dantec Keypoint EMG machine (Dantec, Skovlunde, Denmark). A train of five square wave stimuli 0.5 ms in duration was delivered at 4 ms (250 Hz) interstimulus intervals. Stimulating electrodes consisted of 9 mm gold-plated disc electrodes at C3C4 (International 10–20 system) affixed with collodion. Stimulation output was increased from 50 mA in steps of 5 mA until a reproducible MEP was elicited. The intensity was then increased and fixed at 10% above this threshold intensity to obtain a supramaximal MEP response. Each stimulator was capable of delivering a maximum output of 100 mA (200 mA in total). MEP recordings were obtained with 13 mm disposable subdermal needles (Technomed Europe, Beek, Netherlands) in the tibialis anterior (TA) bilaterally. Filter settings were set at 10 Hz and 2 kHz. Input impedance of stimulating and recording electrodes were maintained below 5 kΩ.
For induction of anesthesia, sodium thiopentone at 4 mg/kg and fentanyl at 2 mcg/kg was administered; 0.8 mg/kg of intravenous atracurium was used to facilitate endotracheal intubation. No further doses of neuromuscular blocking agents were used subsequently. In the desflurane group, anesthesia was maintained using 60% nitrous oxide in oxygen. Desflurane was introduced through a calibrated vaporizer up to an end-tidal concentration of 2.1–4.3 %, with a mean concentration of 3.4% (approximately 0.5 maximum alveolar concentration). This was measured using an Ohmeda respiratory gas monitor 5250 (BOC Group, Louisville, USA). Closed circuit mechanical ventilation was adjusted to maintain end-tidal carbon dioxide levels between 32 and 35 mmHg.
In the TIVA group, anesthesia was maintained using the regime of 10 mg/kg of propofol for the first 10 min, 8 mg/kg for the next 10 min and 5 mg/kg for the subsequent length of operation; 50% air in oxygen was administered. In both groups, morphine was titrated as required for pain relief.
Monitoring included electrocardiography, pulse oximetry, capnography and direct radial artery pressures. All patients were kept nornothermic with a warming blanket. Normotensive anesthesia was maintained throughout the operation.
After approximately 45 min post-induction, a train of four-twitch assessment was performed using a nerve stimulator (Fischer Paykel NS242, UK). Cortical stimulation was commenced only when the amplitude of the fourth was visibly similar to the first. An interval of 3–5 min was allowed between two trains of cortical stimulation. This alternated with monitoring of somatosensory evoked potentials from posterior tibial nerve stimulation.
We measured two parameters: MEP amplitude, onset latency and initial stimulation intensity. Peak to peak amplitudes (between two largest peaks opposite in polarity) and onset latency was utilized for all MEP responses recorded bilaterally. Hence, ipsilateral MEPs refer to MEPs recorded from the TA on the same side as cortical stimulation. Within each patient, ten consecutive supramaximal MEPs obtained before insertion of pedicle screws used as a baseline were averaged to obtain the first two parameters. The initial stimulation intensity was defined as the minimal intensity required to obtain five consistent visible MEP responses at a vertical gain of 20 μV per division.
During insertion of pedicle screws and instrumentation, a 50% reduction of MEP amplitude or 10% prolongation of latency was brought to the surgeon’s attention.
Statistical analyses using Student’s t-tests were obtained with Microsoft SPSS for Windows Version 10.1. Statistical significance was considered at P < 0.05.
Results
There were no complaints of headache, seizures or skin burns postoperatively; all patients had normal neurological examination.
MEPs were successfully obtained from all patients with TA recordings bilaterally. There were four patients in the TIVA group and five in the desflurane group. Mean ages for desflurane (16.2) and TIVA (15.7) groups were not significantly different (P = 0.6).
None of the patients had MEP amplitude or latency changes exceeding our set limits so as to require immediate surgical attention during and after pedicel screw insertion and spinal instrumentation.
The ipsilateral MEP amplitudes (standard deviation) were significantly larger than contralateral MEP amplitudes [68.9 (27.1) vs. 52.5 (15.7) μV, P < 0.01, paired t-test]. The initial stimulation intensity to obtain ipsilateral MEPs was significantly lower than for contralateral MEPs [66.9 (12.3) vs. 74.4 (10.1) mA, P < 0.05, paired t-test]. However, there were no significant latency differences for ipsilateral and contralateral MEPs [32.0 (2.1) vs. 31.5 (2.0) ms, P = 0.3, paired t-test).
There was no significant difference between use of TIVA or desflurane anesthesia for MEP amplitudes obtained, with ipsilateral (P = 0.06, unpaired t-test) and contralateral (P = 0.09, unpaired t-test) stimulation. Additionally, there was also no significant difference between right and left sided MEP amplitudes, either with ipsilateral (P = 0.9, paired t-test) or contralateral (P = 0.7, paired t-test) stimulation.
We consecutively studied an additional 17 subjects monitored for scoliosis surgery using an identical protocol (1 men, mean age 16.1 years, range 14–22). All had the TIVA anesthetic regimen. With right cortex stimulation, mean initial stimulation intensity to obtain ipsilateral MEPs [39.7 (9.9) mA] was significantly lower than to obtain contralateral MEPs [47.1 (11.3) mA, paired t-test, P < 0.0005]. With left cortex stimulation, similar findings were obtained [40.6 (10.7) vs. 50.3 (11.8) mA, paired t-test, P < 0.0005]. With right cortex stimulation, mean ipsilateral MEP amplitudes [107.1 (35.7) μV] were significantly larger than mean contralateral MEP amplitudes [90 (37.1) μV, paired t-test, P = 0.01]. With left cortex stimulation, similar findings were again observed [112.1 (37) vs. 82.3 (30.9) μV, paired t-test, P = 0.0004]. With right cortex stimulation, mean ipsilateral MEP latencies [30.2 (2.4) ms] were not significantly different from mean contralateral MEP latencies [30 (2.3) ms, paired t-test, P = 0.3). With left cortex stimulation, similar findings were again observed [30 (2.1) vs. 30.4 (2.3) ms, paired t-test, P = 0.2].
Examples of MEPs obtained with both ipsilateral and contralateral stimulation are shown in schematically in Fig. 1 and 2.
Fig. 1Schematic diagram showing right cortical stimulation, resulting in ipsilaterally and transcallosally conducted corticospinal impulses activating the spinal cord anterior horn cell. The right ipsilateral MEP recording is from the TA. Summation of ipsilaterally conducted and transcallosally generated descending impulses may thus result in larger ipsilateral MEPs from right cortical stimulationFig. 2Actual consecutive MEPs obtained from a patient, showing larger amplitude responses with ipsilateral stimulation. Both recordings were made from the TA at 70% stimulation intensity
Discussion
The present study showed that ipsilateral MEPs have significantly larger amplitudes and were elicited with significantly lower stimulation intensities than contralateral MEPs. However, onset MEP latencies were not significantly different.
The origin of ipsilateral MEPs in humans is not well understood. In animal studies, cat corticospinal neurons have been shown to evoke ipsilateral actions via ipsilaterally descending reticulospinal tracts, as well as via contralaterally descending reticulospinal neurons, both by synapsing spinal interneurons [9]. Tracer studies in rhesus monkeys have quantified ipsilateral corticospinal fibers as approximately 9–12% of the total descending corticospinal projections [14]. Thus, current evidence points to contralateral corticospinal fibers as the predominant pathway for spinal motorneuron activation.
The presence of ipsilateral MEPs has mostly been described in pathological conditions. Patients with congenital mirror movements [11], schizencephaly [12], and Kallmann’s syndrome [13] show ipsilateral MEPs, which likely result from abnormal structure and function of ipsilateral corticospinal fibers. However, functional reorganization and unmasking of ipsilateral corticospinal pathways may contribute to the generation of ipsilateral MEPs after adult stroke [6] and congenital hemiparesis [18]. One study involving 50 normal children suggested that presence of ipsilateral MEPs might be a normal state of ontogeny. Their disappearance after 10 years old is likely due to increasing transcallosal inhibitory influences [16]. In our study, all patients were above 10 years of age, and did not have clinical features to suggest presence of underlying conditions mentioned above. Another study comparing healthy adults with stroke patients has suggested ipsilateral MEPs may be conducted via corticoreticulospinal or corticopropriospinal pathways in normal subjects [1].
What are the possible underlying mechanisms, which explain our findings? Firstly, it is possible that ipsilateral MEPs may be solely due to transcallosal stimulation of the contralateral motor cortex. Additionally, the effects of anesthesia on corticospinal excitability may facilitate this, hence resulting in significantly lower initial stimulation intensity to obtain ipsilateral MEPs. While evidence to suggest this is scarce, rat brain studies have demonstrated widespread action of anesthesia at multiple binding sites [8]. Magnetic resonance brain imaging has also demonstrated increased callosal T2 changes with anesthesia, suggesting structural alterations at a molecular level [19]. It is also possible that longstanding scoliosis has led to spinal cord plasticity changes. Motor pathway reorganization and spinal cord plasticity have been well documented in response to cord injury [7] in an activity-dependent manner [10]. Thus, structural and postural changes of longstanding scoliosis may have resulted in reorganization of cortical or subcortical motor pathways, including ipsilateral corticoreticular fibres leading to our observations [17]. However, lack of lateralization of MEP amplitudes with ipsilateral or contralateral stimulation was not supportive of this hypothesis.
Additionally, lack of significant ipsilateral and contralateral latency differences suggest bilateral motor cortex stimulation has resulted in ipsilateral MEPs, which may have comprised early ipsilaterally conducted components and late transcallosally stimulated components (Fig. 1). This might also explain the larger amplitudes of ipsilateral MEPs obtained than MEPs derived from contralateral motor cortex stimulation. Further studies clarifying the predominant mechanisms responsible would be interesting.
Are ipsilateral MEP responses useful and relevant in clinical settings? Ipsilateral MEPs are readily elicited, as shown in this study. While the relative contributions of ipsilaterally and transcallosal conducted MEPs remain uncertain, bilateral MEP recordings during spinal surgery IOM may provide additional information regarding the integrity of descending motor tracts. Together with the electrophysiological findings presented here, future studies clarifying these aspects would be justified. It thus may be feasible to routinely monitor MEPs bilaterally in future IOM protocols for spinal surgery.

intraoperative monitoring
ipsilateral
motor evoked potential
scoliosis
contralateral
corticospinal


A 57-year-old man who developed arthritis during R-CHOP chemotherapy for non-Hodgkin lymphoma

Rituximab is a chimeric human-mouse anti-CD20 monoclonal antibody, which is used in the treatment of both B-cell lymphomas and rheumatic diseases. We describe a case of a previously healthy 57-year-old man developing arthritis while being treated with rituximab-CHOP chemotherapy (R-CHOP) for a non-Hodgkin lymphoma. The remittant arthritis developed at successively shorter time-intervals after R-CHOP administration and only improved after rituximab was removed from the chemotherapy schedule, suggesting a rituximab-related phenomenon, as extensive diagnostic testing ruled out any other diagnosis.
Introduction
Rituximab is increasingly used in the treatment of both B-cell lymphomas as well as rheumatic diseases. Several side-effects of rituximab are known, but until now only two reports described the development of arthritis after rituximab therapy [1, 2]. Here we describe yet another case.
Case
A 57-year-old man was referred to the out-patient clinic of rheumatology because of arthritis of the right knee and left wrist.
The patient had been in perfect health until he noticed a swelling of 2.5 cm under his right jaw. He was referred to a specialized oncology center where he was diagnosed with an aggressive follicular B-cell non-Hodgkin lymphoma (NHL) stage IVA with involvement of submandibular and mesenteric lymph nodes and bone marrow. Treatment was instituted with R-CHOP chemotherapy, which consists of cyclophosphamide, doxorubicin, vincristine, prednisone, and rituximab, given at a 3-week interval. During this treatment, granisetron (Kytril®) was given and occasionally magnesiumoxide and paracetamol. Because this patient suffered from a low tumor burden, no tumor lysis profylaxis, i.e., allopurinol was prescribed.
Two and a half weeks after the first course of R-CHOP, the patient developed arthritis of his right knee and left wrist without morning stiffness or involvement of the small hand joints. He had no history of arthralgia, joint swelling, preceding trauma, fever, or infection nor did he have a history of inflammation of the eyes, Raynaud phenomenon, photosensitivity, sicca-syndrome, or inflammatory back pain. The further medical history disclosed several tick bites the year before, with a skin reaction. He rarely used alcohol (maximum of two glasses a day). Family history revealed no rheumatic diseases.
Physical examination showed a profusely swollen and painful right knee and left wrist. The other joints were not afflicted.
Laboratory testing before the start of chemotherapy showed no abnormalities besides a erythrocyte sedimentation rate (ESR) of 21 mm/h. At the time of presentation with arthritis, there was ESR of 41 mm/h, C-reactive protein 256 mg/l, leucocytes 11.1 × 109/l, a normal liver and kidney function, and an IgM-rheumatoid factor (RF) 7 IE/ml, anti-cyclic citrulline peptide (a-CCP) <1 AU/ml, anti-nuclear factor (ANF) negative, and urate of 0.25 mmol/l. A diagnostic puncture of synovial fluid from the right knee was performed, which revealed an inflammatory arthropathy (cell count 5,300/mm3, 14% lymphocytes, 8% mononuclear cells, and 78% granulocytes) with no signs of malignant cells or crystals. Microbiological testing (Gram-stain, Ziehl–Neelsen, and culture) of the synovial fluid showed no microorganisms. X-rays of both knee and wrist did not show bone involvement or chondrocalcinosis. The patient was treated with naproxen (500 mg, twice daily), with which both pain and swelling of the joints were reduced but not completely resolved.
Four days after the second course of R-CHOP, the pain and swelling returned in all its severity and spontaneously regressed after 1 week.
Shortly after the third course of R-CHOP, the patient experienced the same painful joint swellings, now also involving the left knee. This was in spite of intra-articular kenacort injections and prednisone maintenance therapy (10 mg daily), which was started between the courses of chemotherapy. Repeated pathological and microbiological testing of synovial fluid showed no new results.
After these three courses of R-CHOP, the effect on the NHL was evaluated and disclosed that the intra-abdominal NHL-mass was somewhat reduced, and the remnant of the submandibular lymph node had disappeared.
Since the causal relationship between the (activity of) arthritis and the courses of R-CHOP and rituximab being the only component of R-CHOP of which the development of arthritis is described after the administration of this drug [1, 2], the decision was made to give the fourth and fifth course of chemotherapy without rituximab. This time there was no increase in pain or swelling of the joints.
Well over a year after the first R-CHOP chemotherapy, the patient is fully recovered. Evaluation of his NHL shows a near complete remission, and no further treatment was indicated. The arthritis has fully resolved.
Discussion
Arthritis developing during the course of R-CHOP chemotherapy is very unusual. The arthritis developed after successively shorter time-intervals after the R-CHOP administration while no arthritis occurred when CHOP was given without rituximab. This suggests a probably rituximab related, immune-mediated phenomenon. We were not able to detect antibodies against rituximab or immune complexes that might strengthen this diagnosis. However, we did have strong arguments against the other differential diagnoses.
The pattern of arthritis in this patient is unusual for a rheumatoid arthritis; moreover, both IgM-RF and a-CCP were negative, while X-rays made of the afflicted joints disclosed no erosions.
Spondylarthropathy very rarely develops after the age of 45 years. Moreover, inflammatory back pain was absent, and positive arguments for an infection causing reactive arthritis were lacking.
Other autoimmune diseases like systemic lupus erythematosus (SLE) or Sjögren’s syndrome were also very unlikely looking at the clinical presentation, the absence of characteristic signs and symptoms, and the absence of the specific autoantibodies.
A crystalarthropathy is a more likely candidate, as treatment of NHL can cause tumor lysis syndrome, which can give rise to gout. However, serum values of urine acid were repeatedly very low, and there where no other signs of tumor lysis syndrome. Moreover, repeated samples of synovial fluid failed to show any crystals, kidney function was normal; the patient barely used alcohol and did not use diuretics.
The X-rays of both the right knee and left wrist did not show signs of chondrocalcinosis.
Latent infections provoked by the administration of R-CHOP were considered. However, repeated cultures, Gram-stain, and Ziehl–Neelsen of synovial fluid did not disclose any bacteria or yeasts. Serologic testing for Borrelia Burgdorferi, Lues, Chlamydia trachomatis, Parvovirus B19 and PCR on Mycobacteria tuberculosis and Chlamydia trachomatis (both performed in the synovial fluid) proved to be negative.
A wide spectrum of autoimmune manifestations, among others arthritis, is described in NHL [3]. However, arthritis is unlikely in this patient as autoimmune manifestation, as it developed during R-CHOP and the NHL responded well to this chemotherapy.
Furthermore intra-articular localization of NHL was considered. However, both primary and secondary intra-articular localization of NHL is very rare [4], and the fact that more than one joint is afflicted in this patient makes it even more unlikely. Moreover, magnetic resonance imaging (MRI) of both knees did not show tumor mass, and repeated punctures of synovial fluid of both knees did not show any malignant cells. On top of this, a computed tomography (CT) scan of the abdomen revealed regression of the mesenteric NHL-tumor mass after chemotherapy, which means that in the case of any presumed intra-articular localization of NHL, one would expect relapse of joint involvement in the course of chemotherapy instead of progression.
An arthroscopy was considered but not performed because of the risks of infection in this immunocompromised patient, and the low expectancy of achieving the diagnosis by performing the arthroscopy as the presence of NHL intra-articular was considered to be very unlikely.
Because our patient received high dosages of prednisone, the diagnosis of avascular bone necrosis was considered but ruled out by a MRI of both knees. None of the other medications our patient used are known to give arthritis.
Ruling out the above-mentioned diagnoses and taking into account the relationship in time between the development of arthritis and the gifts of R-CHOP, one or more of the components of R-CHOP seem to be the most likely cause of the arthritis in our patient. Of all of the components of R-CHOP, only rituximab is known to be able to give arthritis [1, 2].
Pijpe et al. described the development of arthritis in three patients who received rituximab for primary Sjögren’s syndrome. All of these patients had developed human antichimeric antibodies (HACAs), which suggests an immune-mediated mechanism. Only one other patient tested positive for HACAs but was asymptomatic. The significance of HACAs being present is actually not quite sure as other studies show HACAs being present without specific clinical manifestations [5, 6] or show HACAs being present but later becoming undetectable [6].
Repeated blood tests of our patient did not show any HACAs. The precise mechanism of action in the development of arthritis in our patient is still unknown.
In conclusion, we describe a patient developing severe oligo-arthritis at successively shorter time-intervals after receiving CHOP-rituximab for a NHL. The arthritis is probably caused by an immune-mediated reaction to rituximab. As it is to be expected that rituximab will be used more frequently in future to treat both NHL as rheumatological diseases, we think it is important for physicians to be aware that rituximab may cause severe (oligo-)arthritis as a side effect.

arthritis
lymphoma
rituximab
adverse effects


Use of recommended medications after myocardial infarction in Austria

Guidelines recommend long-term use of beta-blockers (BB), statins, and angiotensin-converting-enzyme-inhibitors or angiotensin-receptor-blockers (ACEI/ARB) after myocardial infarction (MI), but data on their use after discharge are scarce. From Austrian sickness funds claims, we identified all acute MI patients who were discharged within 30 days and who survived ≥120 days after MI in 2004. We ascertained outpatient use of ACEI/ARBs, BBs, statins, and aspirin from all filled prescriptions between discharge and 120 days post MI. Comorbidities were ascertained from use of indicator drugs during the preceding year. Multivariate logistic regression was used to evaluate the independent determinants of study drug use. We evaluated 4,105 MI patients, whose mean age was 68.8 (±13.2) years; 59.5% were men. Within 120 days after MI, 67% filled prescriptions for ACE/ARBs, 74% for BBs, and 67% for statin. While 41% received all these classes and 34% two, 25% of patients received only one or none of these drugs. Older age and presence of severe mental illness were associated with lower use of all drug classes. Diabetics had greater ACEI/ARB use. Fewer BBs were used in patients with obstructive lung disease. Statin use was lower in patients using treatment for congestive heart failure (all P < 0.001). We conclude that recommended medications were underused in Austrian MI survivors. Quality indicators should be established and interventions be implemented to ensure maximum secondary prevention after MI.
Introduction
Cardiovascular disease is among the leading causes of premature death and morbidity in most Western societies. Fortunately, the prognosis of myocardial infarction (MI) has steadily improved over the past decades: case fatality after MI has decreased and long-term survival has increased [1–3], likely due to the introduction and increasing availability and use of acute invasive and non-invasive interventions as well as the introduction of powerful medications for secondary prevention [4].
Among the medications for long-term secondary intervention, aspirin, beta-receptor blockers (BB), 3-hydroxy-3-methyl-glutaryl-co-enzyme-A inhibitors (statins), and angiotensin converting enzyme (ACE) inhibitors have drawn the most attention. More recently, angiotensin receptor blockers (ARB) have become available for use in those patients who develop adverse events from ACE inhibitors; ACE inhibitors and ARBs have been shown to be equally efficacious and effective after MI [5–7].
All these interventions are highly efficacious in reducing the recurrence of MI, the subsequent use of coronary interventions, or the risk of death, and have been demonstrated to be highly attractive economic investments from a societal perspective [8–11]. Practice guidelines recommend the use of these medications for secondary prevention in patients with unstable angina or MI, regardless whether the MI is associated with ST-elevation [12–14]. Considerable variation has been observed, however, in the use of these beneficial interventions [3, 15–17], which has prompted the establishment of quality of care indicators in some countries with the goal to monitor appropriate use of these interventions during hospitalization, at discharge, and during outpatient follow-up after such an event [18–20]. Most relevant in the long run, however, is the outpatient use of these medications after discharge from MI. Several studies have indicated that these drugs are underused for secondary prevention. Most of these investigations were conducted in North America [21–23] and in Europe [24–29]. No such systematic assessment has been conducted in the Austrian health care system except for a small local study [30]. We sought to fill this void by studying proportions of BB, statin and ACE inhibitor or ARB use after MI in a large period cross-section of Austrian MI patients.
Methods
Data sources
Austria is a social welfare state that mandates universal health care to its residents [31]. Patients are assigned membership in one of several sickness funds dependent on their type and location of current or former employment. At the time covered by this study, there were 20 sickness funds in Austria; among those, the 9 provincial sickness funds covering more than three quarters of all residents (6.2 Mio. of 8.2 Mio. overall; data from 2004). Most inpatient and outpatient medical services are covered and each service encounter generates a claim to the health care system. Inpatient services are not paid directly by sickness funds, but by a separate entity, which, however, is partly funded by these. Thus, sickness funds are also informed about each encountered inpatient care. Similarly to most western health care systems, datasets provided by hospitals contain diagnosis codes, admission and discharge dates. Access to prescription drugs is equal across sickness funds and all medications that are deemed efficacious by a national panel are reimbursed. The copayment for medicines per package was €4.25 in 2003, €4.35 in 2004 and €4.45 in 2005. Packages of chronic medications usually contain 28, 30, or 50 pills. Sickness fund premiums, other coinsurance and copayments vary slightly, and indigent patients can apply for waiver of the usually modest copayment for prescription drugs. Few medications are subject to prior authorization by the sickness funds. Prescription claims contain a unique identifier for the specific drug, the dose, and the quantity dispensed.
Study population
For the purpose of this study, we used the complete claims data of individuals covered by several of these sickness funds: the provincial sickness funds (Gebietskrankenkasse) of Vienna, Lower Austria, Upper Austria, Styria, Burgenland, and Carinthia, as well as the funds covering all federal employees (Bundesversicherungsanstalt, BVA) and farmers (Sozialversicherung der Bauern, SVB), respectively. Cumulatively, these sickness funds cover approximately 6.1 million members of the total Austrian insured population of 8.2 million. Each sickness fund separately identified from their insurance claims all patients who were hospitalized and discharged with a primary diagnosis of acute MI in 2004 (International Classification of Diseases, ICD-9: 410.xx; ICD-10: I21) and provided us with their relevant anonymized health care claims data covering the period from January 1, 2003 to June 30, 2005. We only studied each patient’s first hospitalization for MI (including direct transfers from one hospital to another) and required that the admission date be between January 1, and December 31, 2004. We retained only those patients whose hospitalization exceeded 3 days and who were admitted at an acute care hospital. Including patients who were hospitalized <4 days would open up the possibility of wrongly selecting patients into the study sample who had not experienced an MI (e.g., whose MI was ruled out or patients who were admitted for a diagnostic or therapeutic intervention and still coded for acute MI). Our approach of identifying patients with MI has been validated in similar claims data and found to be highly accurate (positive predictive value: 94%) [32]. Since we were interested in medication use after MI, we generated a uniform outcomes ascertainment window and required all patients to be discharged within 30 days and to have survived for ≥120 days from their initial admission date (=index date). We also excluded those patients whose hospitalization occurred at a non-acute care hospital.
Outcomes: use of recommended medications after myocardial infarction
From all filled prescriptions, we recorded out-of-hospital use of several medications between date of discharge and 120 days after MI admission: aspirin, beta-blockers, statins, and ACE inhibitors or ARBs. We also assessed the total number of distinct medications that patients received among statin, BB, and ACE inhibitor/ARB (minimum 0; maximum 3). Since aspirin was available for a price that was below the amount of the drug copayment (€4.35), it is possible that insurance claims data may lead to under-ascertainment of aspirin use. Thus, we decided to investigate aspirin separately, and only among patients who had their copayment waived based on income grounds. These indigent patients had a clear economic incentive to fill prescriptions for aspirin via the prescription route, thus generating a claim to the sickness fund.
Covariates
We created variables indicating each patient’s age in 2004, gender, the length of stay for their index admission, and whether a patient had their prescription copayments waived during the study period (NoCopay vs. Copay). Since claims from outpatient encounters did not contain any diagnosis codes, we ascertained medication use in the 365 days prior to the index date as proxies for several comorbidities using the anatomic therapeutic chemical (ATC) classification system: oral antidiabetic drugs, insulin, antigout medications, several cardiovascular drug classes (alpha blockers, BBs, calcium channel blockers, ACE inhibitors, ARBs, other antihypertensives, diuretics, nitrates, digitalis, vitamin K-antagonist, statins, fibrates), medications indicated for asthma or chronic obstructive pulmonary disease (COPD; inhaled corticosteroids, beta-receptor agonists), drugs reducing gastro-esophageal reflux or ulcer disease (histamine-H2-blockers, proton pump inhibitors, sucralfate, antacids), pain medications (including non-steroidal anti inflammatory drugs, selective COX-2 inhibitors, opioids, and others), oral corticosteroids, and several psychoactive drug classes (benzodiazepines or anxiolytics, antidepressants, antipsychotics). We also recorded the number of hospital days during the year prior to the index date (categorized into: no hospitalization, 1–7, 8–21, and >21 days).
Statistical analysis
We plotted the unadjusted proportions of medication use for the overall population as well as by copayment status along with the corresponding 95% confidence intervals (CIs). We then used univariate and multivariate logistic regression to estimate the crude and multivariate adjusted odds of receiving a given study medication. Since none of our outcomes were rare, we were able to create full multivariate models that included all variables regardless of their statistical significance. In large datasets where outcomes are not rare, full multivariate models are superior to parsimonious models, because they provide better control for residual confounding compared to more restricted models. Odds ratios (OR) were presented with their 95% CIs. Additionally, we showed the population distribution of the number of different study drug classes received among statin, BB, and ACE inhibitor/ARB (minimum 0; maximum 3). Multivariate ordinal logistic regression and linear regression were used to model the associations between covariates and the number of drugs received. All analyses were conducted in the full final study population as well as after restriction to new users of each study drug, i.e. patients who had not received the respective study drug in the year prior to admission for MI. We used the SAS for Windows (release 9.2) software for all statistical analyses (The SAS Institute, Cary, NC).
Results
Study population
We first identified 8,416 hospitalizations with a discharge diagnosis indicating an MI. After excluding all repeat MI hospitalizations and those that occurred before or after 2004 (N = 1,977; 23.5%), we also excluded those patients who died within 120 days after admission for MI (N = 1,221; 14.5%). After further restricting the sample to those patients whose index hospitalization was ≥4, but ≤30 days and excluding admissions at non-acute care hospitals, we obtained a final study sample of 4,105 patients (48.8% of the original hospitalization sample drawn). The mean age was 68.8 years (standard deviation, SD: ±13.2), and 2,442 (59.5%) patients were men. Age differed considerably by gender: men (median: 66 years, interquartile range: 56–75) were substantially younger than women (median: 76 years, interquartile range: 67–82; P < 0.001). Overall, 654 (15.9%) had their prescription copayments waived on the grounds of low income (Table 1). On average, they had been hospitalized for 6.7 (±14.7) days in the year prior to their MI and the mean length of stay for their index admission was 10.9 (±5.3) days. The proportions of selected prescription drugs used in the year prior to admission for MI are listed in detail in Table 1.
Table 1Characteristics of study population (N = 4,105)VariableCount (%) or mean (±SD)Age68.8 (±13.2)    <50 years402 (9.8)    50–69 years1,515 (36.9)    70–89 years1,225 (29.8)    ≥90 years963 (23.5)Male gender2,442 (59.5)Length of stay10.9 (±5.3)Days of hospitalization in prior year6.7 (±14.7)    None2,500 (60.9)    1–7 days595 (14.5)    8–21 days612 (14.9)    ≥21 days398 (9.7)Copayment waived654 (15.9%)Previous medication use    Alpha blocker243 (5.9)    ACE-inhibitor or ARB1,853 (45.1)    Beta-blocker1,454 (35.4)    Calcium channel blocker809 (19.7)    Other antihypertensive734 (18.0)    Diuretic927 (22.6)    Nitrate1,032 (25.1)    Digitalis347 (8.5)    Acetylsalicylic acid1,169 (28.5)    Clopidogrel or Ticlopidine385 (9.4)    Vitamin K-antagonist249 (6.1)    Statin1,043 (25.4)    Fibrate116 (2.8)    Oral hypoglycemic 620 (15.1)    Insulin265 (6.5)    Uric acid lowering drug559 (13.6)    Pain medication1,934 (47.1)    Gastroprotective drug1,584 (38.6)    Asthma/COPD610 (14.9)    Corticosteroid379 (9.2)     Benzodiazepine or anxiolytic491 (12.0)    Antidepressant623 (15.2)    Antipsychotics190 (4.6)
Secondary prevention after myocardial infarction
Within 120 days of their admission for MI, 3,037 (74.0%; 95% CI: 72.6–75.3%) patients filled a prescription for a BB, 2,745 (66.9%; 95% CI: 65.5–68.3%) for an ACE inhibitor or an ARB, and 2,736 (66.7%; 95% CI: 65.3–68.1%) received a statin (Fig. 1). Indigent patients who were not required to pay a copayment received more ACE inhibitors or ARBs (74 vs. 65.5%; P < 0.001), and slightly fewer statins (63.2 vs. 67.2%; P = 0.03), while the proportion of BB use was similar to patients without such a waiver (P = 0.86).
Fig. 1Proportions of medication use after myocardial infarction
The distribution of number of distinct drug classes received in this population was as follows: 1,692 patients (41.2%) received a BB, statin, and an ACE inhibitor or ARB, while 1,391 (33.9%) received two of these drugs. Six hundred and sixty (16.1%) patients received only one of the study drugs whereas 362 (8.8%) patients received none of these medications for secondary prevention at all. This distribution did not differ between patients with vs. without copayment requirement (P = 0.33). The number of drugs received was slightly higher among men compared to women (2.1 vs. 2.0; P = 0.02) and decreased with higher age (P < 0.001). Among the 654 patients with waived copayment, 464 (71%) filled a prescription for aspirin within 120 days of admission for MI.
Independent predictors of study medication use
Age was an independent predictor of recommended medication use after MI: compared to patients younger than 50 years, those between 70 and 89 years had 48% greater odds of receiving ACE inhibitors or ARBs (OR: 1.48), whereas the oldest patients (≥90 years old) were least likely to receive these drugs (OR: 0.73; Table 2). Similarly, these oldest patients were also markedly less likely to receive BBs and statins (Tables 3 and 4). Number of days spent in the hospital in the year preceding the MI admission, a marker of preexisting comorbidity, was consistently and inversely associated with lower use of all these recommended medications (all P for trend <0.001). Patients who had their copayments waived were more likely to fill a prescription for an ACE inhibitor or an ARB after discharge from MI than patients with copayment required (OR: 1.35; 95% CI: 1.10–1.67), but BB or statin use did not differ between these groups. Angiotensin converting enzyme inhibitor or ARB use was further independently associated with previous calcium channel blocker use, use of an oral antidiabetic drug, and prior use of antipsychotic drugs (Table 2). Beta-receptor blockers were more likely to be used in patients who had used other antihypertensive medications prior to MI (Table 3). Lower use of BBs was observed in patients who had received diuretics, vitamin K-antagonist, insulin, antipsychotics, as well as in those patients who received inhaled medications for asthma or COPD (Table 3). Medications that were inversely associated with statin use were diuretics, digitalis, clopidogrel, vitamin K-antagonist, and antipsychotics (Table 4).
Table 2Independent determinants of ACE-inhibitor or ARB useVariableAll patients (N = 4,105)New users (N = 2,252)OR95% CIOR95% CIAge<50–Referent–Referent50–691.190.96–1.491.230.96–1.5870–891.481.19–1.851.541.19–2.00≥900.730.59–0.900.790.60–1.03Male gender1.070.91–1.251.190.98–1.44Length of stay1.021.00–1.031.031.01–1.05Hospital days*0–Referent–Referent1–70.680.56–0.840.620.49–0.808–210.790.63–0.990.680.51–0.91>210.510.39–0.680.530.35–0.79Copayment waived1.351.10–1.671.341.03–1.74Alpha-blocker1.070.75–1.531.270.73–2.20ACE-inhibitor or ARB5.674.74–6.78––Beta-blocker1.120.94–1.331.160.93–1.45Calcium channel-blocker1.351.10–1.661.341.01–1.79Other anti-hypertensive agents0.990.80–1.211.120.85–1.47Diuretic0.850.68–1.050.870.65–1.18Nitrate0.880.72–1.070.820.63–1.08Digitalis1.150.84–1.571.040.65–1.65Aspirin0.890.74–1.070.910.70–1.18Clopidogrel0.900.68–1.200.730.46–1.15Vitamin K-antagonist0.990.70–1.411.100.65–1.87Statin1.120.92–1.380.840.63–1.11Fibrate1.210.76–1.931.000.56–1.77Oral antidiabetic1.261.00–1.581.060.79–1.44Insulin1.020.73–1.441.200.68–2.10Asthma/COPD1.070.86–1.341.100.83–1.47Benzodiazepines/anxiolytics1.060.83–1.361.160.83–1.62Antidepressants0.870.70–1.090.850.64–1.13Antipsychotics0.640.45–0.910.650.41–1.04* P for trend <0.001Table 3Independent determinants of beta-blocker useVariableAll patients (N = 4,105)New users (N = 2,651)OR95% CIOR95% CIAge <50–Referent–Referent50–691.250.98–1.601.210.93–1.5970–891.050.83–1.331.140.87–1.47≥900.620.51–0.760.540.43–0.69Male gender1.140.97–1.351.190.98–1.43Length of stay1.000.98–1.011.000.98–1.01Hospital days *0–Referent–Referent1–70.920.74–1.150.850.66–1.088–210.770.61–0.960.780.60–1.02>210.570.44–0.750.610.43–0.84Copayment waived1.090.89–1.351.190.93–1.53Alpha-blocker1.541.07–2.201.731.12–2.67ACE-inhibitor or ARB1.221.02–1.451.160.94–1.41Beta-blocker4.363.55–5.35––Calcium channel-blocker1.291.05–1.591.491.16–1.90Other anti-hypertensive agents0.830.68–1.010.870.69–1.10Diuretic0.800.65–0.980.770.60–0.99Nitrate1.030.84–1.261.040.81–1.33Digitalis0.790.60–1.040.680.48–0.96Aspirin0.960.79–1.160.880.70–1.12Clopidogrel0.790.59–1.070.650.43–0.97Vitamin K-antagonist0.670.49–0.930.440.29–0.66Statin0.940.76–1.160.850.67–1.10Fibrate1.140.70–1.861.210.65–2.25Oral antidiabetic1.060.85–1.321.070.82–1.39Insulin0.720.53–0.980.780.52–1.16Asthma/COPD0.670.55–0.830.630.49–0.80Benzodiazepines/anxiolytics1.331.04–1.711.270.94–1.72Antidepressants0.880.71–1.090.960.74–1.24Antipsychotics0.710.51–1.000.740.50–1.09* P for trend <0.001Table 4Independent determinants of statin useVariableAll patients (N = 4,105)New users (N = 3,062)OR95% CIOR95% CIAge <50–Referent–Referent50–691.381.09–1.761.401.09–1.8170–891.080.86–1.361.090.85–1.39≥900.390.32–0.470.370.30–0.46Male gender1.100.94–1.291.130.95–1.35Length of stay0.980.97–0.990.990.97–1.00Hospital days*0–Referent–Referent1–70.880.71–1.090.820.66–1.048–210.680.55–0.850.680.53–0.87>210.480.37–0.630.470.34–0.65Copayment waived1.090.89–1.341.070.85–1.34Alpha-blocker0.890.65–1.221.040.72–1.51ACE-inhibitor or ARB0.980.82–1.161.040.86–1.25Beta-blocker1.080.91–1.291.070.88–1.30Calcium channel-blocker1.010.83–1.230.980.79–1.23Other anti-hypertensive agents0.970.80–1.180.970.78–1.21Diuretic0.820.67–1.000.790.63–1.00Nitrate0.940.77–1.140.960.77–1.21Digitalis0.600.46–0.800.510.37–0.72Aspirin0.850.71–1.030.740.60–0.92Clopidogrel0.700.51–0.940.610.40–0.94Vitamin K-antagonist0.620.45–0.850.520.35–0.78Statin6.395.03–8.11––Fibrate2.241.36–3.702.311.35–3.97Oral antidiabetic0.950.77–1.180.980.77–1.26Insulin0.760.56–1.040.710.48–1.05Asthma/COPD0.870.71–1.070.840.66–1.06Benzodiazepines/anxiolytics0.890.70–1.120.940.72–1.22Antidepressants1.130.91–1.401.080.85–1.39Antipsychotics0.480.34–0.680.530.36–0.79* P for trend <0.001
Naturally, prior use of a medication class was highly predictive of use of that class after MI in the full study population. Results from the analyses restricted to new users of each study drug were very similar to the full population analyses, albeit with wider confidence intervals (Tables 2–4). Analyses of independent predictors of number of recommended drugs received using linear or ordinal logistic regression confirmed what could be gleaned from the analyses of each drug class: older age, more hospital days in the previous year, indicator drugs for severe heart failure (digitalis, diuretics, vitamin K-antagonist), and antipsychotic use were all independently associated with fewer recommended medications received (results not shown). Gender, however, was not independently associated with number of medications received.
Discussion
In a large population-based study of patients who experienced an acute MI in Austria, we found that ambulatory use of several recommended medications after discharge was suboptimal. Within 120 days after their MI, only 74% patients received a BB, 67% a statin, and 67% filled a prescription for an ACE inhibitor or ARB. Only 41% of patients received all three interventions, while 25% of patients received only one of these beneficial drugs or even none at all. Underuse of these medications is unfortunate from both a patient’s and a societal perspective: while optimal secondary prevention including these drugs prolongs the expected lifespan of a patient after MI, use of these interventions constitutes an attractive allocation of scarce economic resources. Thus, considerable room for improvement is present in the care of patients after MI in Austria, and interventions ought to be targeted towards increasing the prescribing and use of these medications.
While this is the first large-scale study of the quality of post-MI care in Austria, similar investigations have been conducted in other countries. The most relevant comparison can be drawn with results from the EUROASPIRE studies [27–29]. These studies, three waves have been conducted to date, used surveys to evaluate coronary care in 9 (EUROASPIRE I), 15 (EUROASPIRE II), and 22 (EUROASPIRE III) countries, respectively; Austria did not participate in either of these. The most recent data available are from EUROASPIRE II, which covered the years 1999/2000 [28]. Medication use was assessed at admission, discharge (abstracted from charts), and at least 6 months (from patient interview) after the acute admission or procedure. While some variation was observed across countries, data specifically for after MI drug use was only reported in aggregate across countries. Approximately 74% of MI patients received a BB at discharge and 68% >6 months after the event; these proportions are similar to the 74% observed in our study. For ACEI, the proportions at discharge and >6 months after the event were 49 and 45%, respectively, considerably lower than the 67% observed in Austria. It is unclear, however, whether ARB use was regarded equivalent to ACEIs and included in this quality measure in the EUROASPIRE study. Lipid-lowering drugs were prescribed to 42% of patients at discharge and used by 60% at >6 months after the event, compared to 67% in our study [28].
A comparison of these reports, however, needs to be conducted with caution. Considerable differences exist between these and other studies, especially in their population selection criteria, ascertainment of medication use, and the year(s) studied. Several studies, specifically from the United States and Canada, investigated medication use only in older patients (>65 years) [33]. Results from elderly populations cannot be compared with findings from the general population, since age is a strong predictor of preventive medication use. Studies that measured medication use using discharge notes are likely to overestimate medication use, because patients may not have received a prescription or had chosen to not fill it. The increasing use of the study medications also needs to be taken into consideration and, in this respect, older reports considerably vary with recent ones. To this point, Gislason et al. [24] studied MI patients in Denmark and found that the proportion of patients who received an ACE inhibitor increased from 25% in 1995 to 36% in 2002. Similarly, use of BB increased from 38% to 68% during that time. This study differs from ours in that drug use was ascertained within 30 days following the discharge date from MI. While BB use is roughly similar to our findings, the use of ACE inhibitor was substantially lower in that Danish cohort. Statin or aspirin use was not part of that study, but a separate study using the same Danish database focused on this aspect of post MI care. In this report, statin use was ascertained within 6 months of discharge and increased from 13% in 1995 to 61% in 2002 [34]. This percentage is similar to the statin use of 67% in our Austrian sample, given that our data are slightly more recent; we did, however, use a shorter ascertainment window. Another report studied the use of preventive medications after MI in The Netherlands [26]. The authors confirmed a trend towards increased use of all drug classes from 1991 to 2000, with ACE inhibitor being dispensed to 44%, BB to 76%, and statins to 58% in the most recent study year (2000). Use of these medications was ascertained within 30 days after discharge, but patients were not required to survive for a minimum number of days after discharge to be eligible for study. Taking these study design differences into account, it appears that more patients received a BB after discharge in the Netherlands compared to Austria. Interestingly, neither the Dutch, nor the Danish study took ARB use into consideration as an established substitute for ACE inhibitors. Similarly, data from EUROASPIRE I and II confirms increasing use these preventive medications [29].
In the present study, we also identified several predictors of use for the study medications. In general, patients ≥90 years of age were substantially less likely to receive these recommended medications than younger patients. Similar evidence for under-treatment among the elderly was also found in other countries [24]. This behavior may constitute general treatment bias against very old patients, or reflect that these patients may not live long enough to reap the benefits of long-term preventive interventions. Indeed, specific evidence on the efficacy and cost-effectiveness of the study medications in very old patients is lacking. In general, old patients were excluded from participation in virtually all efficacy trials on which current clinical practice recommendations are based. Only the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial has addressed this issue and specifically studied older individuals. PROSPER demonstrated that statins are efficacious in prevention of coronary events in older patients, but the participants in PROSPER were still “only” 70–82 years at enrollment [35]. Further, statin therapy has been shown to be cost-effective in 75–84 years old patients [36]. We found that those indigent patients who had their copayment waived had at least the same level of medication use compared to relatively more affluent patients who were responsible for the copayment portion of their prescription (€4.35), thus indicating that such a waiver successfully removed the economic barriers to filling these prescriptions. Of note, patients whose copayment was waived were more likely to be women and previous recipients of antipsychotic drugs, but otherwise similar to those who were required to pay a copayment (detailed results not shown).
The number of hospital days in the year prior to MI was a strong negative predictor of medication use for all classes. This might reflect greater comorbidity or frailty in these patients, which both have been associated with lower use of and persistence with preventive medications. Similarly, patients receiving antipsychotic drugs had a lower likelihood to receive the study medications, likely indicating treatment bias regarding the mentally diseased. Beta-blocker use was significantly lower among patients who received any drugs for inhalation that are indicated in asthma or COPD, a plausible pattern, which may reflect presence of a relative contraindication or intolerance by the patient. Indeed, among patients without previous use of such asthma or COPD drugs (N = 3,495), BB use after MI was 75.4% (rather than 74.0% in the overall population), an only slightly higher proportion with respect to the goal of appropriately treating all patients free from contraindications. Statins were less likely to be used in patients who had previously used diuretics, digitalis, or coumadin, possibly indicating congestive heart failure or atrial fibrillation and thus, worse prognosis.
In theory, and barring presence of any absolute contraindications, 100% of patients could receive each of these medications. Clearly, the actual proportion that could be attained in practice is lower than that, since some patients will have an absolute contraindication for any given drug. For ACEI/ARBs, this number would be very low, since the only absolute contraindication (other than pregnancy) is history of angioedema, whose incidence is below 1% among new ACEI users [37]. Beyond this, relative contraindications may exist such as hyperkalemia or advanced chronic kidney disease, but in most patients, at least a low-dose trial of an ACEI/ARB should be attempted with appropriate clinical and laboratory monitoring in place, possibly in combination with a loop diuretic. Similarly, for statins, practically every one should receive this treatment and absolute contraindications are either very rare (active liver disease) or not to be expected in this MI population (pregnancy, lactation). Thus, at least an attempt at using statins and ACEI/ARB in post-MI patients can be expected in probably >95% of patients. The situation is slightly different with BBs, since more contraindications exist whose classification as absolute vs. relative are uncertain [38]. Cardiogenic shock, hypotension, and certain bradycardic arrhythmias untreated with a pacemaker certainly constitute absolute contraindications, whereas a treatment attempt in patients with stable obstructive lung disease should be conducted. From our dataset, it is difficult to ascertain most of these conditions, but when eliminating all patients who had received inhalative corticosteroids or beta mimetics, the percentage of BB users increased slightly to 75.4% from 74.0% in the overall population.
This report needs to be read with several limitations in mind. Aspirin was available at a price below the copayment for prescription medications. Thus, aspirin use may be underascertained in non-indigent patients. We were, however, able to assess aspirin use in those patients who had their copayment waived and found that 71% of patients received this drug. While we cannot be certain that medications received in the pharmacy were actually taken by these patients, our way of ascertaining medication use is superior to other methods. Compared to notes in medical charts, patients may not fill the prescriptions they were given. In surveys, patients may report what they perceive as being desirable rather than their actual behavior. Both methods, may lead to inaccurately optimistic estimates of medication use. In our study, comorbidities were not ascertained from diagnosis codes, but rather from typical medications that are given for several comorbidities. It has been shown that the information from diagnosis codes and from medication claims provides only marginally inferior confounding control in administrative datasets [39]. On a similar note, we were unable to ascertain reliable information on contraindications for the study drugs. Since most of these contraindications are relative rather than absolute contraindications [37, 38] this aspect may be of minor importance. While not fully population based, our data differ from other studies in that a wide range of hospitals and typical care settings were studied rather than single departments in predominantly academic medical centers. We consider our data generalizable to the population level, since three quarters of the Austrian population were included in the study, and the preponderance of patients omitted (1.2 Mio.; data from 2004) was excluded because they lived in the three Western provinces (Salzburg, Tyrol, Vorarlberg), whose sickness funds did not participate in our data collection effort. The remaining patients that we were unable to capture were members of very small corporate sickness funds, railroad and mining workers, as well as self-employed individuals; all those, however, received care at the same hospitals and by the same physicians as the enrolled patients. Finally, the analytical dataset did not contain linkable pseudoanonymized hospital identifiers. Thus, we were unable to study variations in treatment behavior across the provider level. It has been shown that provider preference can be a stronger determinant of treatment received than actual patient level indications [40].
In summary, we provide evidence for underuse of several recommended medications after MI as recently as 2004 in the Austrian healthcare system. Our observations are in line with findings from other European and North American healthcare systems, despite the differences in data collection and time period studied. Educational efforts need to be directed at both physicians and patients, and the implementation of quality indicators should be considered. Maximizing secondary prevention after MI is highly desirable from an individual patient and the societal perspective.

angiotensin converting enzyme inhibitors


Requirements regarding dose rate and exposure time for killing of tumour cells in beta particle radionuclide therapy

Purpose The purpose of this study was to identify combinations of dose rate and exposure time that have the potential to provide curative treatment with targeted radionuclide therapy applying low dose rate beta irradiation.
Introduction
Many types of tumour overexpress cell surface-associated antigens or receptors suitable as targets for radionuclide therapy, and many types of targeting agent have been suggested or are already being applied for such therapy. This therapy is currently employed for lymphomas [1, 2] using radiolabelled antibodies and also for neuroendocrine [3–5] and paediatric tumours [6, 7] using radiolabelled somatostatin analogues and meta-iodobenzylguanidine (mIBG), respectively. In the majority of these cases, beta emitters such as 90Y, 131I and 177Lu have been applied. The results have, so far, essentially shown palliative effects [1, 8–12], and there is hope that combinations of beta particle emitters, e.g. 90Y and 177Lu, will improve the therapy results [13].
The cell-killing capacity of low LET radiation, i.e. photons and electrons, is well known when applying high dose rates, typically 0.5–2.0 Gy/min, as in external radiotherapy [14, 15]. However, the extensive experimental and clinical knowledge on the effects of external radiotherapy can be deployed to only a limited extent in understanding the effects of radionuclide therapy. A major difference is that the dose rate in radionuclide therapy is at least two orders of magnitude lower than in external radiotherapy [10, 16–19]. The lower dose rate allows for DNA repair and repopulation during the radiation exposure, which is not the case during high dose rate exposures. Basic radiobiological studies have shown that low dose rates, in the range of 0.1–1.0 Gy/h, give a much lower biological effect (per dose unit) than high dose rates in the range 0.5–2.0 Gy/min [15, 17, 20, 21]. It is also known that an inverse dose rate effect exists in that dose rates of 0.2–0.4 Gy/h can give more cell kill than dose rates in the range 0.7–1.0 Gy/h [15, 22].
Only crude estimates can be made from previous experiments to elucidate which combinations of low dose rate and exposure time can cure a metastasis containing, for example, 105 cells. Cell survival has most often been analysed after a cell cloning 1–2 weeks after the radiation exposure. For example, a total dose of about 30–50 Gy, given with 0.1–1.0 Gy/h, seems necessary to decrease the single cell survival probability to 10−5 [23, 24], and thereby give a reasonable chance of killing 105 tumour cells. Furthermore, targeted radionuclide therapy is complicated, since it is not enough only to consider the macroscopic dose concept; different cellular and intracellular distributions of radionuclides can give different biological effects although the macroscopic dose is the same [25, 26].
One way to obtain solid information on which combinations of low dose rate and exposure time can give curative treatments with beta particles (which also is low-LET radiation) is, of course, through experiments and clinical trials. In this study we used an experimental model with the criterion that the low dose rate beta radiation must kill all 105 tumour cells in a culture dish in order to simulate a successful treatment. The follow-up period was 3 months.
The choice of 105 tumour cells is somewhat arbitrary and is based on two arguments. The first is that this number represents a small tumour cell cluster that normally cannot be identified by routine diagnostic procedures such as computed tomography or magnetic resonance imaging (unless the tumour cells cause macroscopic changes in the surrounding normal tissues). Furthermore, this number of tumour cells in most cases does not cause symptoms in the patient. Thus, a cluster of 105 tumour cells in a patient can be considered an “occult” or “subclinical” tumour or metastasis. The second argument is more practical, since the presence of 105 tumour cells in a normal cell culture dish or flask allows enough space for exponential growth and, at the same time, frequent cell–cell contacts.
Our ambition was not to simulate the dose rate variations in time and space that occur in radionuclide therapy. In the clinical setting, the dose rate varies with time, not only as a consequence of the physical half-life of the radionuclides, but also due to time-dependent changes in their spatial distribution [16, 17, 24, 26, 27]. Factors of importance are ongoing vascularisation processes, variations in vessel wall leakage and changes in blood flow. There are probably also various diffusion and convection conditions in different areas of tumours, resulting in variable penetration properties of the radiolabelled targeting agents. In addition, there might be variations in the expression of target structures on the tumour cells. All these time-dependent factors make it difficult to establish basic and reproducible dose rate–response relations in vivo.
Our experimental model was designed to give reproducible and controllable irradiation conditions, and we applied a model with a rather long physical half-life (32P sources with T1/2=14.3 days), giving only a slow decrease in dose rate during the exposures. Relevant dose rates were selected through the amount of radionuclide placed in the irradiation chambers. The exposure times were selected to correspond to the effective half-lives of the radionuclides delivered by targeting agents of different types.
In targeted radionuclide therapy it is, of course, also necessary to consider unwanted side-effects on normal tissues. However, analyses of normal tissue effects were beyond the scope of this study. Hyperradiosensitivity [28, 29] at low doses, bystander effects [30–32] and low dose rate-induced apoptosis [33, 34] are all extensively studied processes. Our model allows these processes to work together, but we did not try to study them separately. The overall goal of the study was to find “dose rate–exposure time” relations that could kill all of the exposed 105 tumour cells, so that no remaining cells would be observed after 3 months.
Materials and methods
Irradiation chambers
The irradiation chambers have been described previously [35], so only a short description is given here. Three identical chambers were used and each was filled with 400 ml distilled water containing 0.74–2.22 GBq 32P. The water was boiled and degassed shortly before adding 32P and filling of the chambers, in order to avoid air bubbles. The beta emitter 32P (orthophosphate) (T1/2=14.3 days) was obtained from Amersham Pharmacia Biotech (Amersham, UK).
The upper area of the chambers, where the cells were exposed to beta particles from 32P, was covered with a 0.5-mm thin transparent polycarbonate foil. The radiation protection walls surrounding the side and the bottom of the chambers, as well as the lid above the cell cultures, consisted of 15-mm transparent polycarbonate (Macrolon). 32P could not reach and be incorporated in the cells. The irradiated cells were grown in 3-cm-diameter culture dishes with a plastic bottom thickness of 1 mm. The culture dishes were placed directly on the thin foils above the 32P source. The chambers were kept in cell culture incubators at 37°C (Kebo Assab T304GF, Stockholm, Sweden) and supplied with 5% carbon dioxide. The lid above the cultures had side openings, allowing efficient passage of the incubator atmosphere.
Dosimetry
The dosimetry has also been described previously [35]. The dose rate for each chamber was controlled by measurements with a thin-walled parallel ion chamber [36]. The ion chamber was calibrated using an external 60Co source with the front wall of the ion chamber at the dose maximum depth, where the dose rate was 0.30 Gy/min. The 60Co source was calibrated according to national standard procedures accepted for radiotherapy purposes. The thin-walled parallel ion chamber accurately measured the dose independent of dose rate down to at least 0.01 Gy/h, if corrections were made for “leakage current” in the instrumentation.
The measurements of dose rates were performed with the thin-walled ion chamber placed in cell culture dishes standing on the 32P radiation chambers. This procedure allowed mimicking of the dose rate in the cell environment. All three chambers were measured repeatedly. Measurements were also made with a surface hand detector (RNI 10/R Intensimeter, Nuklex, Uppsala, Sweden), and a calibration curve was constructed to facilitate repeated dose rate determinations during the cell culture periods.
Tumour cells
The cells used were HT-29 colorectal adenocarcinoma, A-431 cervical squamous carcinoma, SKBR-3 breast cancer, all from the American Type Culture Collection (ATCC), and the two gliomas U-118MG and U-373MG from the Department of Pathology, Uppsala University, Uppsala, Sweden. They were grown in Ham’s F-10 medium supplemented with 10% fetal bovine serum, 2 mmol/l L-glutamine, 100 μg/ml streptomycin and 100 U/ml penicillin, all components from Sigma AB (Stockholm, Sweden). The cells were normally grown in an incubator of type Galaxy S (LabRum Klimat AB, Stockholm, Sweden), and during the irradiations they were grown in a similar incubator (Kebo Assab T304GF, Stockholm, Sweden). Both incubators were run at 37°C and supplied with 5% carbon dioxide.
The cells in the study were selected for the following reasons. SKBR-3 cells are often studied since they express large amounts of HER2 receptors and are therefore applied in experiments on HER2-directed radionuclide targeting, using antibodies or affibody molecules [37, 38]. A-431 cells express both large amounts of EGFR and also rather large amounts of HER2 and are therefore often studied for radionuclide targeting with both EGF ligands [39] and anti-HER2 antibodies [40]. Both cell types are planned for experimental therapy using beta particle-mediated radionuclide therapy, especially 177Lu. The two glioma cell lines also express EGFR [41] to some degree but were, together with the HT-29 cells, selected because they have recently been studied at our laboratory with regard to short-term effects after low dose rate irradiations [35]. It was found that U-373MG cells showed radiation-induced apoptosis, while U-118MG cells did not. The HT-29 cells were intermediate in this respect [35]. Furthermore, U-373MG cells have previously been reported not to show hyperradiosensitivity at low doses, while both U-118MG and HT-29 cells do [28].
Choice of dose rate and exposure time
In the previous study, with the same 32P chambers, we analysed effects on cells after exposure to initial dose rates of only 0.05–0.09 Gy/h for 7 days [35]. The cells in that study were analysed for effects on cell number, apoptosis and cell cycle block at day 7 of continuous exposure. However, we also allowed cells to continue to grow for longer times in parallel dishes and found that all cultures recovered. Thus, we decided to apply initial dose rates from 0.1 Gy/h up to 0.8 Gy/h in the present study to have a reasonable chance of “simulating” curative treatment. We could not apply higher dose rates because of regulatory rules limiting the amount of 32P that could be handled in the cell culture laboratory. Furthermore, this dose rate range is the same as that applied in published studies on low dose rate effects [21–23], hyperradiosensitivity and low dose rate [29], and radionuclide treatment of gliomas in vitro [42] and in vivo [43], and actually covers the range up to the highest dose achievable in targeted radionuclide tumour therapy [10, 16, 18, 27, 44].
Four cell dishes were placed in each irradiation chamber when the dose rate was as expected and the cells were then kept there for 24, 72 or 168 h (1, 3 or 7 days). The radiation exposure time was chosen not to be longer than a week, since it is known from numerous articles in the field of radionuclide therapy that the tumour cell retention of radioactivity is generally in the range of some days up to about 1 week (in some cases it is only a few hours). Furthermore, it is well known that the biological half-life of tumour targeting agents (ligands, antibodies and antibody fragments) in the systemic circulation is often shorter than a week (in the case of small ligands, it is only a few hours). Thus, the longest exposure time considered to be realistic was 1 week.
Cell counting
The medium was removed from the cell dishes and the cells were quickly washed with 0.5 ml trypsin-EDTA (0.25% trypsin/0.02% EDTA solution in PBS, VWR, Stockholm, Sweden) and then incubated with 0.5 ml trypsin-EDTA (37°C, 5% CO2) until the cells detached. Next, 1.5 ml medium was added to each dish and the cells resuspended to a single cell solution. For cell counting, 19.5 ml PBS (pH 7.4) was added to 0.5 ml cell suspension and an electronic cell counter was used (Coulter Z2, 7–20 μm, Beckman Coulter, Stockholm, Sweden).
Cell culture conditions during and after irradiations
Cells were seeded sparsely in culture dishes (diameter 3.5 cm, surface 9.6 cm2, Nunc, Roskilde, Denmark) a few days before the start of the radiation exposure. They were seeded so that each culture dish contained about 105 cells at the start of the exposure. The first cell count was made at the start of each experiment, on representative culture dishes. If the cell number was about 105 per dish, four other, parallel culture dishes were placed in each of the three irradiation chambers. The irradiated cells were grown in the chambers with unirradiated control dishes placed on a near radiation-shielded shelf in the same incubator. The cells did not reach confluence during the irradiation period. After the radiation exposure, the cells were moved from the irradiation chamber incubator to another incubator and the cell growth was followed for several months. At the first subcultivation after the radiation exposure, the cells were transferred from culture dishes to culture flasks (25 cm2, Nunc, Roskilde, Denmark), and these flasks were then used throughout the growth period. The medium in all culture dishes and flasks was replaced three times a week. Cell counting was in most cases performed once a week, followed by reseeding of 105 cells in each new flask.
Growth curves
The growth curves were constructed as if all cells had been saved at each subcultivation. By calculating how many cells would have been obtained if all cells had been saved, such high cell numbers as 1015 (Fig. 1a) and even up to 1025 (Fig. 1b) were obtained. In reality, repeated dilutions were made to keep the number of cells in each culture flask in the range of 105–106, thus allowing for exponential growth. Four parallel flasks were kept for each experiment. In order to analyse the significance of the differences between the groups, t tests were performed.
Cell kill versus regrowth
The criterion for killing of a cell culture with 105 cells was that no living cells could be seen in the phase contrast microscope and that no regrowth was observed after at least 3 months of follow-up, also applying electronic cell counting.
Growth delay
Growth delay was also analysed after 1, 3 or 7 days of continuous low dose rate exposure. The growth curves of the irradiated samples in some cases did not have the same slope as the control curves, so it was not possible to wait and measure growth delay when the recovered cells and the control cells had a similar growth rate. Instead, growth delay was defined as the time it took for the irradiated cells to reach the cell number 1010 in relation to the time it took for the control cultures to reach this number.
Literature survey
The Medline-based PubMed database was used to survey effects of targeted radionuclide therapy and of low dose rate therapy.
Results
Growth curves
Figure 1 shows examples of growth curves for control cells and cells exposed to continuous low dose rate beta irradiation. In Fig. 1a the initial dose rate was 0.415 Gy/h and the exposure time 72 h. After 72 h the dose rate had decreased to 0.359 Gy/h, and the exposure gave a total dose of about 27.8 Gy. The irradiated HT-29 cells recovered after irradiation and resumed, after about 50 days, a similar growth rate as the controls. In contrast, the U-373MG cells completely ceased to grow after the same radiation exposure. After more than 30 days, only a few giant cells could be identified in the microscope. They were too few to be counted with the electronic cell counter. However, there was a possibility that at least a few of these cells could grow later, so they were observed (with normal medium changes) for up to 3 months. Nevertheless, no recovery could be observed; instead, the cells disappeared. It was then concluded that the irradiation procedure had killed all U-373MG cells. Thus, the HT-29 cultures survived the treatment, while the U-373MG cells died.
Fig. 1Examples of cell growth as a function of time after exposure to low dose rate irradiation. a HT-29 and U-373MG cells were exposed to 0.415 Gy/h as the initial dose rate and then continuously exposed for 72 h. b A-431, U-118MG and SKBR-3 cells were exposed to 0.806 Gy/h as the initial dose rate and then continuously exposed for 24 h. Mean values and maximal variations from four parallel samples are given
Figure 1b shows examples of growth curves for an initial dose rate of 0.806 Gy/h and an exposure time of 24 h. After 24 h the dose rate had decreased to 0.768 Gy/h and the exposure gave a total dose of about 18.9 Gy. The irradiated A431 cells continued to grow, but at a slower rate than the controls. The growth of irradiated U-118MG cells was arrested for up to about 40 days after the treatment. During those 40 days, resting cells were observed in the culture flasks, but there was no sign of growth. After 40 days a few mitotic cells were observed in the phase contrast microscope, and the number of cells was thereafter measured with the electronic cell counter. A clear regrowth was seen after 60 days. However, their growth rate was slower than that of the corresponding controls. The SKBR-3 cells looked severely damaged (fragmented, decreasing in number and forming giant cells) some days after the exposure and were too few to be counted with the electronic cell counter. Within 1 month, no surviving cells could be observed in the culture flasks. In this case, too, we continued to control the culture flasks for 3 months (with normal medium changes) and found that there were no remaining cells in these cultures. Thus, A-431 and U-118MG cells survived, while the SKBR-3 cells died.
The conclusions from the examples in Fig. 1a and b are that four different responses were observed:
The HT-29 cells recovered to the control growth rate after a growth delay.The U-118MG cells recovered after a growth delay but continued to grow at a slower rate than the controls.The A-431 cells continued to grow without delay but at a slower rate than the controlThe U-373MG and SKBR-3 cells died.
Cell kill and regrowth versus dose rate and exposure time
Figure 2 summarises cell-killing and regrowth results from all performed low dose rate experiments. All five analysed cell types were irradiated with different initial low dose rates (0.1–0.8 Gy/h) and were continuously exposed for 1, 3 or 7 days.
Fig. 2Summary of all low dose rate experiments carried out for a U-118MG, b U-373MG, c HT-29, d A-431 cells and e SKBR-3 cells. The cells were irradiated with different initial dose rates and were then exposed to the radiation for 1, 3 or 7 days. The figures show at which combinations of dose rate and exposure time all cells were killed (area with no survivors), and at which at least some cells survived and displayed regrowth (the regrowth area). The separation between the two areas is indicated by bold solid lines. The total delivered radiation dose (Gy) is given in parentheses near each point. The 20-Gy isodose curve is indicated by a dashed line
Figure 2 parts a–e show a similar and general pattern. When applying 7 days of continuous irradiation, low initial dose rates, about 0.2–0.3 Gy/h, were enough to kill all cells. When cells were exposed for only 3 days, a dose rate in the order of 0.4–0.6 Gy/h was necessary to kill all cells. Only the SKBR-3 cells were killed after 24-h exposure to about 0.8 Gy/h. As mentioned in Materials and methods, higher dose rates could not be used in these experiments, so we do not know how high the dose rates would have to be during 24-h exposure in order to kill the other cell types. It was found that the regrowth pattern was the same in all four flasks.
However, even if the results looked rather similar and independent of cell type, there were some cell type-dependent differences. The U-118MG cells (Fig. 2a) required, during 7 days’ exposure, at least about 0.3 Gy/h as the initial dose rate to be completely growth inactivated. The U-373MG cells (Fig. 2b) were completely growth inactivated after an initial dose rate of only about 0.15 Gy/h and 7 days’ exposure. Thus, the U-373MG cells were, in these cases, easier to kill than the U-118MG cells. Considering all cells, it seemed that the U-118MG cells were most resistant and U-373MG and SKBR-3 most sensitive, while A-431 and HT-29 were intermediate.
Cell kill and regrowth versus total dose
The 20-Gy isodose curve is drawn with a dashed line in Fig. 2a–e. For U-373MG and SKBR-3 cells, at least a total dose of 20 Gy was necessary to prevent regrowth. For HT-29 and A-431 cells an even higher total dose seemed necessary, and for the resistant U-118MG cells it seemed that total doses of at least 40 Gy were necessary to prevent regrowth.
Growth delay as a function of dose rate
Figure 3a–e shows growth delays versus the initial dose rate after 1, 3 or 7 days of continuous low dose rate exposure. The growth delay curves in Fig. 3a show that the radioresistant U-118MG cells had growth delays, after 24-h exposure, which increased slowly as a function of the initial dose rate. A growth delay of 2 months was obtained at about 0.7, 0.3 and 0.2 Gy/h after 1, 3 and 7 days of continuous exposure, respectively. The growth delay curves for the more radiosensitive U-373MG cells increased more steeply (Fig. 3b), and a growth delay of 2 months was obtained at about 0.5 and 0.2 Gy/h after 1 and 3 days of continuous exposure, respectively. Thus, the U-373MG cells were more sensitive than the U-118MG cells also with regard to growth delay.
Fig. 3Growth delay versus the initial dose rate after 1, 3 or 7 days of continuous low dose rate exposure for a U-118MG, b U-373MG, c HT-29, d A-431 and e SKBR-3 cells. The boxes at the top of each figure indicate at which dose rates and exposure times there was no regrowth (infinite growth delay or total kill of the cultures). Mean values and maximal variations from four samples are shown
Both the HT-29 cells (Fig. 3c) and the SKBR-3 cells (Fig. 3e) had a biphasic growth delay curve after 1 day’s exposure. The A-431 cells (Fig. 3d) had a slow increase in growth delay as a function of dose rate after 1 day’s exposure.
The SKBR-3 cells had a growth delay that increased rather steeply as a function of the dose rate and reached a value of 2 months at about 0.50 and 0.15 Gy/h after 1 and 7 days of continuous exposure, respectively (Fig. 3e).
Growth delay as a function of total dose
The same growth delay data as in Fig. 3a–e are instead plotted as a function of the delivered total dose in Fig. 4a–c, but here, for clarity, without the maximal variations. In all cases, there was a general increasing growth delay as a function of dose. Growth delays in the order of 10 days were obtained for all cells after delivery of total doses in the range 5–15 Gy, independent of whether the dose was given during 1, 3 or 7 days. Delays around 100 days required total doses of about 15–20 Gy when given during 1 day and 25–40 Gy when given during 3 or 7 days, for all cells.
Fig. 4Growth delay versus total dose after a 1, b 3 or c 7 days of continuous low dose rate exposure for U-118MG, U-373MG, HT-29, A-431 and SKBR-3 cells. The growth delay values are the same as in Fig. 3 but, for clarity, without maximal variations
Discussion
The obtained results can hopefully serve as a guideline for the combinations of dose rate and exposure time necessary to kill tumour cells when applying low dose rate beta irradiation. The shift from regrowth to “cure” (no surviving cells) fell, for each cell type, within a narrow range of combinations.
The U-118MG cells were more resistant to the treatments than the U-373MG and SKBR-3 cells. The A-431 and HT-29 cells showed intermediate resistance. However, the differences between the cell lines were not dramatic, and it can be generally stated that when applying 7 days of continuous irradiation, initial dose rates of about 0.2–0.3 Gy/h were enough to kill all cells in the cultures. When exposed for 3 days, an initial dose rate in the order of 0.4–0.6 Gy/h was needed. When the cells were exposed for only 24 h it was not possible to kill all the cells (with the exception of SKBR-3 cells), even if the initial dose rate was as high as about 0.8 Gy/h.
The studied dose rates are the highest that can be achieved in targeted radionuclide therapy [10, 16, 18]. The total doses achieved after 1, 3 or 7 days’ exposure also correspond to the highest achievable doses in targeted radionuclide therapy [16], and most often total doses of no more than 10–20 Gy are obtained in targeting of B-cell lymphomas [19]. However, there are indications from preclinical studies that dramatic “dose amplification” per receptor interaction can be achieved by using effective residualising agents [45].
The obtained dose rates in beta particle-based radionuclide therapy are to a large extent a consequence not only of the amount of radionuclides bound to each tumour cell, but also of the cross-fire effect. This means that radionuclides bound to one cell also irradiate nearby cells owing to the long range of the radiation [44, 46]. This can increase the dose rate tenfold, and makes it reasonable to assume that dose rates in the range used in our model experiments can be achieved in tumours in patients. The dose rate will be lower for a single tumour cell considering only the radionuclides bound to that cell [25]. Beta particles with a long range will permit rather uniform dose distributions and hopefully deliver therapeutically relevant radiation doses also to non-targeted tumour cells.
Lower dose rates than we applied will probably not lead to curative treatments when beta particles are applied. From the obtained results it is obvious that, at least for the five types of tumour cell tested, we succeeded in finding “dose rate–exposure time” combinations that could distinguish between “cure” (killing of 105 tumour cells) and “relapse” (recovery of tumour cells).
There may be cases in which only a fraction of the tumour cells have to be killed directly by radiation, since the remaining tumour cells may be killed through bystander effects [30–32] or other factors (e.g. limited nutrition supply, natural immune response, adjuvant chemo- or immunotherapy). However, our model can be applied under the assumption that 105 tumour cells have to be killed by radiation, even if other tumour cells are killed by other means.
When considering radionuclide therapy it is, of course, also important to consider unwanted effects on normal tissues. The tolerance doses for most normal tissues are not known when exposure is to low dose rate irradiation. Targeted radionuclide therapy, using, for example, radiolabelled antibodies, fragments of antibodies or various receptor ligands, is expected to result in highly tumour-specific uptake of the therapeutic radionuclides. Thus, for a curative intent it is reasonable to establish the necessary tumour dose rates and exposure times. Another obvious question is which targeting agent should be tried for each type of tumour and, most importantly, whether the required conditions can be achieved without excessively severe side-effects on normal tissues. However, analyses of effects on normal tissues were beyond the scope of this study.
Here we discuss the observed cell type-dependent differences. In a previous study [35] we published data on low dose rate acute effects, using three of the cells in the present study: U-118MG, U-373MG and HT-29. In that study the initial dose rate was only 0.05–0.09 Gy/h and the exposure time, 7 days. As would be expected in view of our new data, all cultures did grow after such treatment. It was shown that the U-373MG cells had, at day 7, the most pronounced reduction in cell number owing to a combination of a G2 block and radiation-induced apoptosis. There were surprisingly low reductions in U-118MG and HT-29 cell numbers. U-118MG had a G2 block but no radiation-induced apoptosis. HT-29 had both a G2 block and some radiation-induced apoptosis, but the amount of apoptosis was smaller than for U-373MG cells. Thus, the results from that study indicated the U-373MG cells to be more sensitive than the other two cell lines owing to a higher degree of apoptosis. This is in agreement with the cell-killing results from the present study.
The intrinsic radiosensitivity measured as S2Gy, after exposure to a high dose rate (most often 0.5–2.0 Gy/min) photons has previously been determined for four of our studied cell lines. No determination of S2Gy for SKBR-3 cells was found in the literature. The results are given in Table 1 [28, 47–54].
Table 1Survival at 2Gy after exposure to high dose ratesCell lineSurvival at 2GyReferencesU-118MG0.44–0.70[28], [47]U-373MG0.60–0.62[28], [48], [49]HT-290.55–0.78[28], [50], [51], [52], [53], [54]A-431≈0.52[53]
There is also a review article on the intrinsic radiosensitivity, measured as cell survival at the dose 2Gy, S2Gy, for 694 human cell lines, of which 271 were from tumours [55]. The tumour cell lines were grouped according to tumour type, and the S2Gy values for the U-118MG and U-373MG gliomas and the A-431 cervical carcinoma used in this study fell within the expected range of values for the corresponding types of tumour. Thus, these cells can be considered typical for their tumour groups, at least regarding intrinsic radiosensitivity at high dose rate exposure. The HT-29 colorectal carcinoma is an exception, since it seems to be somewhat more radioresistant than most other colorectal carcinomas.
Considering the values in Table 1, it is clear that there is no relation between S2Gy and the effects of low dose rate irradiations. For example, the U-118MG cells were found to be most radioresistant to a low dose rate, while their S2Gy values were in the same range as for the other cell lines. The U-373MG cells, which were considered most sensitive to a low dose rate, also had S2Gy values in the same range.
One possible explanation of the lack of agreement between intrinsic radiosensitivity measured as S2Gy and the effect of a low dose rate is that there are cell type-dependent differences in repopulation during low dose rate irradiations. Such differences can probably “overshadow” the differences in intrinsic radiosensitivity. Another possible explanation might be cell type-dependent differences in the capacity for low dose rate-induced apoptosis. The latter is supported by our previous study [35], which showed that low dose rate-induced apoptosis was more frequent in U-373MG cells than in HT-29 cells and that no such apoptosis could be observed for U-118MG cells. Furthermore, it seems as if differences in hyperradiosensitivity (measured at low doses but at a high dose rate) are not of great importance, since the U-118MG and HT-29 cells have been reported to show hyperradiosensitivity, while U-373MG cells do not [28]. Had hyperradiosensitivity been of importance under the exposure conditions in this study, then U-373MG cells should have been more resistant than HT-29 and U-118MG cells.
It has recently been suggested that variations in radiosensitivity at low dose rates are related to the compactness of chromatin [56], but it is not known whether the cells in our study have any differences in this respect. In another recent experimental study, a good therapeutic effect at a low dose rate was reported; in fact, if the total delivered dose was in the range 1–2 Gy, the effect was as good as that achieved at a high dose rate, although the difference in dose rate was nearly three orders of magnitude [57]. This indicates that there are basic radiation biology aspects of low dose rate radiation that have to be analysed in much more detail. A clue to the molecular factors involved came from a recent report showing that activation or inhibition of the DNA damage sensor ATM is of importance [58]. It was found that DNA damage inflicted at a low rate failed to activate ATM; however, if ATM was activated by chloroquine, the cells survived the low dose rate much better.
We conclude that dose rates in the range 0.2–0.3 Gy/h are necessary in order to kill 105 tumour cells during 1 week’s exposure. Higher dose rates, such as 0.4–0.6 Gy/h and >0.8 Gy/h, are necessary if the exposure times are only 3 days and 1 day, respectively. If, in some cases, a good therapeutic effect cannot be obtained with beta particle radionuclide therapy because of too low dose rates and/or too short exposure times, then repeated (fractionated) treatment is a possibility to improve the result. However, the cellular response to repeated low dose rate exposures has to be analysed in further studies, since there is a risk of radiation-induced changes in the growth pattern of the tumour cells surviving the first exposure, as shown in Fig. 1b.

radionuclide
low dose rate
tumour therapy
nuclear medicine
radiation effects